PCA_Pizza.R

# carregando as bibliotecas 
suppressPackageStartupMessages(library("plotly"))
suppressPackageStartupMessages(library("tidyverse"))
suppressPackageStartupMessages(library("knitr"))
suppressPackageStartupMessages(library("kableExtra"))
suppressPackageStartupMessages(library("car"))
suppressPackageStartupMessages(library("rgl"))
suppressPackageStartupMessages(library("gridExtra"))
suppressPackageStartupMessages(library("PerformanceAnalytics"))
suppressPackageStartupMessages(library("reshape2"))
suppressPackageStartupMessages(library("rayshader"))
suppressPackageStartupMessages(library("psych"))
suppressPackageStartupMessages(library("ggrepel"))
suppressPackageStartupMessages(library("factoextra"))
suppressPackageStartupMessages(library("sp"))
suppressPackageStartupMessages(library("gridExtra"))

# Carregar dados
pizza <- as.data.frame(read_csv("Pizza.csv"))

## 
## -- Column specification --------------------------------------------------------
## cols(
##   brand = col_character(),
##   id = col_double(),
##   mois = col_double(),
##   prot = col_double(),
##   fat = col_double(),
##   ash = col_double(),
##   sodium = col_double(),
##   carb = col_double(),
##   cal = col_double()
## )

# Apresentando a base de dados:
pizza %>% 
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

brand	id	mois	prot	fat	ash	sodium	carb	cal
A	14069	27.82	21.43	44.87	5.11	1.77	0.77	4.93
A	14053	28.49	21.26	43.89	5.34	1.79	1.02	4.84
A	14025	28.35	19.99	45.78	5.08	1.63	0.80	4.95
A	14016	30.55	20.15	43.13	4.79	1.61	1.38	4.74
A	14005	30.49	21.28	41.65	4.82	1.64	1.76	4.67
A	14075	31.14	20.23	42.31	4.92	1.65	1.40	4.67
A	14082	31.21	20.97	41.34	4.71	1.58	1.77	4.63
A	14097	28.76	21.41	41.60	5.28	1.75	2.95	4.72
A	14117	28.22	20.48	45.10	5.02	1.71	1.18	4.93
A	14133	27.72	21.19	45.29	5.16	1.66	0.64	4.95
A	14101	27.35	21.20	45.59	4.94	1.65	0.92	4.98
A	14108	26.98	21.20	45.03	5.15	1.67	1.64	4.97
A	14164	28.70	20.00	45.12	4.93	1.56	1.25	4.91
A	14154	30.91	19.65	42.45	4.81	1.65	2.81	4.72
A	24005	30.91	20.77	42.03	4.90	1.61	1.39	4.67
A	24026	30.83	17.88	44.33	5.26	1.76	1.70	4.77
A	24094	32.73	20.06	39.74	5.24	1.69	2.23	4.47
A	24108	34.58	17.53	40.87	5.05	1.61	1.97	4.46
A	24102	31.80	20.35	40.44	5.43	1.61	1.98	4.53
A	24082	31.02	19.05	42.29	5.27	1.71	2.37	4.66
A	34017	27.02	19.56	47.20	4.95	1.65	1.27	5.08
A	34020	27.78	20.01	45.59	4.97	1.70	1.65	4.97
A	24136	30.88	20.58	42.26	4.96	1.63	1.32	4.68
A	24122	32.20	19.25	43.42	4.62	1.50	0.51	4.70
A	24115	33.19	18.05	41.88	5.22	1.70	1.66	4.56
A	34012	30.43	19.78	44.20	4.80	1.61	0.79	4.80
A	34006	28.93	19.99	45.20	4.78	1.62	1.10	4.91
A	24146	30.41	18.71	43.99	4.86	1.62	2.03	4.79
A	24138	29.62	21.10	43.37	5.05	1.69	0.86	4.78
B	14015	49.57	13.70	29.07	3.62	1.10	4.04	3.33
B	14006	52.68	14.38	25.72	3.26	0.93	3.96	3.05
B	14024	48.53	13.14	30.38	3.55	0.99	4.40	3.44
B	14052	50.19	13.78	28.39	3.56	1.00	4.08	3.27
B	14062	50.67	13.21	27.66	3.64	1.00	4.82	3.21
B	14047	49.99	13.35	29.20	3.52	1.05	3.94	3.32
B	14074	50.72	12.93	29.88	3.60	1.03	2.87	3.32
B	14083	50.81	12.56	29.95	2.99	0.81	3.69	3.35
B	14094	54.08	13.28	25.25	3.10	0.80	4.29	2.98
B	14124	51.90	14.27	24.92	3.85	1.06	5.06	3.02
B	24019	50.33	13.96	29.25	3.42	0.96	3.04	3.31
B	24012	49.69	13.63	29.59	3.41	0.98	3.68	3.36
B	14132	51.12	14.02	27.37	3.71	1.11	3.78	3.18
B	14146	49.77	13.24	28.91	3.59	1.06	4.49	3.31
B	14149	54.96	14.26	22.99	3.19	0.90	4.60	2.82
B	14161	55.11	14.87	21.90	3.29	0.86	4.83	2.76
B	14113	54.12	14.06	24.95	3.14	0.82	3.73	2.96
B	24008	49.34	13.79	29.57	3.52	0.95	3.78	3.36
B	24029	50.65	13.14	28.79	3.73	1.09	3.69	3.26
B	24045	52.46	14.18	24.60	3.57	1.12	5.19	2.99
B	24040	49.96	13.40	28.84	3.48	0.98	4.32	3.30
B	24093	49.57	13.17	29.39	3.59	1.06	4.28	3.35
B	24083	49.34	13.06	29.46	3.51	1.04	4.63	3.36
B	24049	50.87	13.85	27.64	3.71	1.10	3.93	3.20
B	24101	51.03	13.90	27.56	3.73	1.08	3.78	3.19
B	34011	53.98	14.05	24.73	3.32	0.92	3.92	2.94
B	24125	52.23	13.64	27.04	3.57	0.98	3.52	3.12
B	24145	51.74	13.95	27.75	3.60	1.04	2.96	3.17
B	24151	51.52	13.72	28.28	3.62	1.05	2.86	3.21
B	34005	51.86	13.13	28.82	2.94	0.80	3.25	3.25
B	24118	51.75	13.18	28.38	3.04	0.86	3.65	3.23
C	14058	48.40	26.05	21.40	3.44	0.50	0.71	3.00
C	14022	48.69	28.48	17.37	3.53	0.43	1.93	2.78
C	14036	48.88	25.23	20.89	3.22	0.47	1.78	2.96
C	14093	48.97	25.63	19.28	3.48	0.55	2.64	2.87
C	14080	48.84	23.98	23.37	3.00	0.52	0.81	3.09
C	14029	49.73	25.65	19.98	2.51	0.52	2.13	2.91
C	14106	50.18	28.30	15.79	3.47	0.45	2.26	2.64
C	14014	48.15	27.98	18.69	3.58	0.48	1.70	2.87
C	14073	49.72	27.31	16.89	3.08	0.25	3.00	2.73
C	14151	51.59	26.24	16.41	3.61	0.60	2.15	2.61
C	14162	52.26	26.31	14.77	3.51	0.53	3.15	2.51
C	14139	49.35	25.23	20.03	3.02	0.44	2.37	2.91
C	14115	47.91	26.03	21.54	3.71	0.60	0.81	3.01
C	24006	47.83	25.82	20.79	3.33	0.54	2.23	2.99
C	24020	47.90	25.55	21.10	3.04	0.43	2.41	3.02
C	24031	49.10	24.53	21.08	2.84	0.34	2.45	2.98
C	24038	50.04	24.13	19.75	3.21	0.52	2.87	2.86
C	24043	52.19	26.00	16.64	4.17	0.61	1.00	2.58
C	24152	47.11	26.17	21.29	3.36	0.48	2.07	3.05
C	24144	48.48	26.76	19.99	3.64	0.46	1.13	2.91
C	24135	52.22	26.25	16.45	3.92	0.38	1.16	2.58
C	24124	49.57	26.91	18.00	2.21	0.41	3.31	2.83
C	24113	51.71	24.98	17.20	3.01	0.34	3.10	2.67
C	24058	49.27	27.42	17.42	3.05	0.33	2.84	2.78
C	24091	47.25	23.95	24.24	3.47	0.57	1.09	3.18
C	34010	50.98	26.34	16.47	3.20	0.43	3.01	2.66
C	34003	49.57	25.46	20.79	3.04	0.37	1.14	2.94
D	14092	46.64	21.38	24.96	4.60	0.77	2.42	3.20
D	14081	45.93	21.60	25.87	4.51	0.73	2.09	3.28
D	14072	47.60	22.07	21.13	4.07	0.72	5.13	2.99
D	14116	47.61	22.44	19.61	4.06	0.60	6.28	2.91
D	14128	46.91	21.79	21.17	4.06	0.76	6.07	3.02
D	14107	46.88	21.71	23.60	4.59	0.75	3.22	3.12
D	14050	47.49	21.75	20.83	4.01	0.67	5.92	2.98
D	14013	48.03	21.96	20.88	4.02	0.70	5.11	2.96
D	14004	49.16	27.99	17.49	3.29	0.39	2.07	2.78
D	14003	47.17	22.29	21.30	4.08	0.74	5.16	3.02
D	14037	47.29	21.48	21.69	4.03	0.67	5.51	3.03
D	14023	47.53	21.11	21.54	4.02	0.70	5.80	3.02
D	14059	47.86	22.25	19.53	4.04	0.68	6.32	2.90
D	14163	48.09	22.65	21.59	5.22	0.93	2.45	2.95
D	14150	47.73	22.38	21.39	5.21	0.99	3.29	2.95
D	14140	48.44	22.73	21.05	5.22	0.98	2.56	2.91
D	24007	47.43	22.13	21.01	4.09	0.72	5.34	2.99
D	24021	47.68	21.84	20.45	4.06	0.71	5.97	2.95
D	24011	48.05	22.05	20.57	4.04	0.70	5.29	2.94
D	24030	48.01	21.31	21.05	4.01	0.73	5.62	2.97
D	34009	47.45	22.37	20.97	4.06	0.70	5.15	2.99
D	24039	47.80	22.36	20.39	4.02	0.70	5.43	2.95
D	24044	48.31	22.49	19.53	4.18	0.62	5.49	2.88
D	34004	46.19	21.19	25.18	4.66	0.80	2.78	3.23
D	24153	48.81	22.43	18.68	4.10	0.72	5.98	2.82
D	24143	48.89	22.95	21.93	5.26	0.85	0.97	2.93
D	24134	47.91	22.22	20.40	4.07	0.56	5.40	2.94
D	24123	46.28	21.51	25.44	4.58	0.60	2.19	3.24
D	24114	46.29	21.43	26.00	4.71	0.69	1.57	3.26
D	24084	47.03	20.84	25.68	4.52	0.69	1.93	3.22
D	24092	46.80	20.70	25.10	4.55	0.70	2.85	3.20
D	24043	52.19	26.00	16.64	4.17	0.61	1.00	2.58
E	14089	34.58	7.44	16.24	1.31	0.39	40.43	3.38
E	14056	36.84	7.77	17.07	1.37	0.40	36.95	3.33
E	14099	35.14	8.05	15.77	1.38	0.41	39.66	3.33
E	14033	39.25	8.67	4.44	1.54	0.51	46.10	2.59
E	14063	34.51	7.75	14.87	1.42	0.42	41.45	3.31
E	14029	39.59	8.36	4.39	1.52	0.48	46.14	2.58
E	14039	34.94	7.81	13.67	1.36	0.40	42.22	3.23
E	14142	39.36	8.10	16.44	1.45	0.44	34.65	3.19
E	14122	36.04	7.74	15.49	1.45	0.45	39.28	3.27
E	14078	36.54	7.75	15.67	1.43	0.44	38.61	3.26
E	14126	37.78	8.30	13.05	1.64	0.49	39.23	3.08
E	14109	35.30	7.92	13.85	1.46	0.40	41.47	3.22
E	14155	34.47	7.62	19.07	1.44	0.44	37.40	3.52
E	14160	33.24	7.54	19.56	1.32	0.43	38.34	3.60
E	24110	37.34	7.33	19.61	1.60	0.45	34.12	3.42
E	24088	37.59	7.93	13.58	1.43	0.45	39.47	3.12
E	24053	36.50	7.52	12.46	1.51	0.47	42.01	3.10
E	24110	37.34	7.33	19.61	1.60	0.45	34.12	3.42
E	24035	34.31	7.98	14.54	1.46	0.49	41.71	3.30
E	24099	36.69	7.80	14.77	1.46	0.46	39.28	3.21
E	24140	34.23	7.75	17.94	1.61	0.44	38.47	3.46
E	34031	35.54	7.47	17.67	1.44	0.47	37.88	3.40
E	34030	35.21	6.98	20.02	1.35	0.46	36.44	3.54
E	34032	33.65	7.11	19.50	1.48	0.45	38.26	3.57
E	24142	34.77	7.26	18.80	1.58	0.43	37.59	3.49
E	34033	37.32	7.40	8.18	1.63	0.53	45.47	2.85
E	14126	37.78	8.30	13.05	1.64	0.49	39.23	3.08
E	24104	34.48	7.54	13.93	1.45	0.44	42.60	3.26
F	34037	28.03	7.65	18.39	1.53	0.49	44.40	3.74
F	14054	30.09	7.99	15.16	1.46	0.48	45.30	3.50
F	14118	29.79	8.17	14.35	1.49	0.46	46.20	3.46
F	14110	30.07	8.02	20.39	1.45	0.45	40.07	3.76
F	14096	28.46	7.70	18.88	1.40	0.43	43.56	3.75
F	14079	30.29	8.09	14.82	1.52	0.51	45.28	3.47
F	14065	28.66	7.67	16.12	1.41	0.43	46.14	3.60
F	14084	30.96	8.31	13.42	1.49	0.43	45.82	3.37
F	14018	29.78	8.20	14.51	1.50	0.50	46.01	3.47
F	14038	30.28	7.76	16.04	1.40	0.42	44.52	3.53
F	14152	29.92	8.11	19.23	1.51	0.48	41.23	3.70
F	14143	29.54	7.79	15.08	1.41	0.45	46.18	3.52
F	14130	28.93	8.18	19.35	1.39	0.58	42.15	3.75
F	14165	29.89	7.95	15.08	1.45	0.47	45.63	3.50
F	24035	27.65	7.78	17.30	1.29	0.40	46.25	3.72
F	24049	28.33	7.82	17.96	1.41	0.45	44.48	3.71
F	24042	29.10	8.07	20.05	1.45	0.45	41.33	3.78
F	24046	29.59	8.05	14.07	1.44	0.45	46.22	3.49
F	24055	27.93	7.88	17.49	1.44	0.47	45.26	3.96
F	24086	30.53	8.02	14.17	1.49	0.47	45.79	3.43
F	24097	30.68	8.11	12.92	1.56	0.47	46.73	3.36
F	24103	30.15	8.06	12.23	1.50	0.47	48.06	3.35
F	24109	29.30	8.02	16.34	1.43	0.45	44.91	3.59
F	24150	29.69	7.63	15.71	1.63	0.46	45.34	3.53
F	24157	29.00	7.51	17.78	1.58	0.43	44.13	3.67
F	34035	28.98	7.70	16.67	1.48	0.47	45.17	3.62
F	24106	28.84	7.88	17.21	1.42	0.46	44.65	3.65
F	34036	28.34	7.60	18.51	1.45	0.46	44.10	3.73
F	34034	28.36	7.62	19.29	1.45	0.47	43.28	3.77
F	24137	30.97	7.60	14.22	1.78	0.45	45.43	3.40
G	14145	28.15	8.23	15.45	1.41	0.45	46.76	3.59
G	24015	28.35	8.19	14.90	1.40	0.43	47.16	3.56
G	24004	30.85	8.03	13.67	1.41	0.42	46.04	3.39
G	14095	28.21	8.30	15.00	1.41	0.43	47.08	3.57
G	14153	28.83	8.26	20.10	1.37	0.42	41.44	3.80
G	14017	28.29	8.05	16.72	1.31	0.43	45.63	3.65
G	14010	28.68	8.30	16.07	1.41	0.45	45.54	3.60
G	14055	27.71	8.28	15.62	1.53	0.50	46.86	3.61
G	14040	28.03	8.27	16.40	1.37	0.41	45.93	3.64
G	14026	28.13	8.34	16.19	1.42	0.45	45.92	3.63
G	14119	28.09	8.42	14.06	1.47	0.45	47.96	3.52
G	14131	28.19	8.57	14.16	1.76	0.42	47.32	3.51
G	14112	28.63	8.42	15.24	1.43	0.43	46.28	3.56
G	14077	33.09	7.87	12.07	1.37	0.44	45.60	3.23
G	14066	26.33	8.03	19.98	1.43	0.45	44.23	3.89
G	14085	27.28	8.55	15.18	1.51	0.46	47.48	3.61
G	14166	27.56	8.25	14.65	1.45	0.46	48.09	3.57
G	24022	27.72	8.06	15.34	1.35	0.42	47.53	3.60
G	24041	30.63	8.21	17.33	1.39	0.42	42.44	3.59
G	24047	29.06	8.46	14.12	1.47	0.47	46.89	3.48
G	24033	28.55	8.25	17.30	1.48	0.47	44.42	3.66
G	24119	27.16	8.27	14.68	1.79	0.46	48.10	3.58
G	24121	28.33	8.17	13.64	1.45	0.47	48.41	3.49
G	24156	26.19	7.99	17.53	1.42	0.44	46.87	3.77
G	34008	26.45	7.89	17.97	1.30	0.39	46.39	3.79
G	34018	27.72	8.24	15.16	1.46	0.45	47.42	3.59
G	24059	25.00	8.49	16.87	1.45	0.47	48.19	3.79
G	34013	29.14	8.46	12.25	1.51	0.46	48.64	3.39
G	24149	28.64	8.01	16.02	1.43	0.45	45.90	3.60
H	14127	36.12	8.33	11.90	1.42	0.39	42.23	3.09
H	24001	35.10	8.04	19.07	1.36	0.41	36.43	3.50
H	14144	35.48	7.66	15.39	1.37	0.46	40.10	3.30
H	14123	35.66	9.04	6.24	1.50	0.42	47.56	2.83
H	14111	35.61	8.07	16.15	1.41	0.40	38.81	3.33
H	14088	35.68	8.01	16.36	1.30	0.39	38.65	3.34
H	14028	40.72	8.34	4.96	1.42	0.43	44.56	2.56
H	14009	35.55	7.32	16.40	1.76	0.36	38.97	3.33
H	14007	33.05	7.34	15.78	1.34	0.42	42.49	3.41
H	14057	33.75	8.07	14.93	1.31	0.40	41.94	3.34
H	14032	38.84	8.55	4.38	1.41	0.43	46.82	2.61
H	14100	33.44	7.45	18.49	1.39	0.40	39.23	3.53
H	14041	36.43	8.67	15.05	1.35	0.38	38.50	3.24
H	14064	35.84	7.90	14.09	1.25	0.42	40.92	3.22
H	14076	36.63	8.38	12.59	1.36	0.41	41.04	3.11
H	14159	35.50	8.11	13.45	1.34	0.42	41.59	3.20
H	14156	36.87	7.82	14.58	1.32	0.40	39.41	3.20
H	24009	35.50	7.51	15.63	1.42	0.42	39.94	3.30
H	24016	33.90	7.76	15.84	1.30	0.42	41.20	3.38
H	24024	35.80	7.82	14.08	1.43	0.42	40.87	3.21
H	24089	35.74	7.86	14.27	1.40	0.44	40.73	3.23
H	24054	35.74	7.47	19.14	1.34	0.40	36.31	3.47
H	24037	35.99	8.23	16.60	1.40	0.45	37.78	3.33
H	24034	35.50	7.90	13.83	1.41	0.46	41.36	3.22
H	24120	35.91	7.41	16.41	1.75	0.43	38.52	3.31
H	34028	36.01	7.70	15.60	1.37	0.43	39.32	3.28
H	34007	36.73	7.42	18.16	1.17	0.39	36.52	3.39
H	24139	35.86	7.47	14.72	1.67	0.40	40.28	3.23
H	34029	36.32	8.06	12.54	1.35	0.43	41.73	3.12
H	24100	34.61	7.17	17.88	1.29	0.40	39.05	3.46
H	24132	36.67	7.81	9.34	1.64	0.44	44.54	2.93
H	24112	35.94	7.97	13.50	1.45	0.42	41.14	3.18
H	24089	35.74	7.86	14.27	1.40	0.44	40.73	3.23
I	14134	54.64	10.36	12.89	2.21	0.53	19.90	2.37
I	14046	54.52	9.85	13.55	2.04	0.47	20.05	2.42
I	14019	53.84	10.22	13.05	2.07	0.48	20.82	2.42
I	24107	54.32	10.66	14.04	2.03	0.46	18.95	2.45
I	24111	52.90	10.19	14.35	2.02	0.49	20.54	2.52
I	24128	55.00	11.11	11.30	2.05	0.47	20.54	2.28
I	24052	56.24	9.06	11.49	1.93	0.48	21.28	2.25
I	14068	56.25	9.96	13.22	2.05	0.46	18.52	2.33
I	14157	54.43	9.61	12.18	2.16	0.51	21.62	2.35
I	14158	53.69	11.00	15.23	2.25	0.55	17.83	2.52
I	14102	54.69	10.32	13.77	2.15	0.48	19.07	2.41
I	14103	53.16	11.17	13.83	2.18	0.47	19.66	2.48
I	14031	55.15	10.92	12.51	2.20	0.51	19.22	2.33
I	14067	54.87	10.78	13.65	2.08	0.50	18.62	2.40
I	14030	55.43	10.46	12.37	2.17	0.51	19.57	2.31
I	24023	55.60	9.69	13.89	1.99	0.48	18.83	2.39
I	14114	54.51	9.93	12.66	2.07	0.53	20.83	2.37
I	14098	54.74	10.18	12.60	2.06	0.48	20.42	2.36
I	14125	54.17	10.67	12.18	2.08	0.49	20.90	2.36
I	24048	52.75	10.78	12.98	2.12	0.49	21.37	2.45
I	34023	54.36	11.43	13.09	2.24	0.48	18.88	2.39
I	34022	54.28	10.75	13.87	2.13	0.46	18.97	2.40
I	34021	54.54	10.40	13.22	2.10	0.47	19.74	2.40
I	24141	54.06	10.68	13.53	2.04	0.46	19.69	2.43
I	34019	57.22	9.66	10.95	2.04	0.47	20.13	2.18
I	34027	54.80	10.57	13.42	2.08	0.50	19.13	2.40
I	34026	54.17	10.13	13.25	2.07	0.46	20.38	2.41
I	34025	53.57	10.73	12.78	2.16	0.48	20.76	2.41
I	34024	55.29	9.84	12.91	2.08	0.51	19.88	2.35
J	34042	46.16	10.34	16.14	2.47	0.67	24.89	2.86
J	34045	43.80	10.97	16.49	2.46	0.65	26.28	2.97
J	14044	47.60	10.43	15.18	2.32	0.56	24.47	2.76
J	14045	46.84	9.91	15.50	2.27	0.57	25.48	2.81
J	14042	46.10	9.87	15.97	2.19	0.53	25.87	2.87
J	14043	47.84	10.16	14.56	2.27	0.54	25.17	2.72
J	24065	45.86	10.50	17.07	2.33	0.61	24.24	2.93
J	24064	46.55	10.75	16.72	2.24	0.61	23.74	2.88
J	24063	46.13	10.71	17.24	2.36	0.61	23.56	2.92
J	24062	48.58	9.76	16.01	2.30	0.60	23.35	2.77
J	24074	44.76	12.91	15.56	2.34	0.61	24.43	2.89
J	24073	46.13	10.84	13.99	2.38	0.64	26.66	2.76
J	24072	47.43	10.45	16.50	2.35	0.61	23.27	2.83
J	24071	46.22	11.26	15.93	2.47	0.63	24.12	2.85
J	24068	45.20	10.67	16.38	2.44	0.60	25.31	2.91
J	24078	47.05	10.46	15.16	2.34	0.64	24.99	2.78
J	24056	43.45	10.81	19.49	2.51	0.68	23.74	3.14
J	34038	47.74	10.23	16.31	2.50	0.67	23.22	2.81
J	34041	45.17	10.42	17.20	2.34	0.61	24.87	2.96
J	34040	44.77	10.52	16.12	2.44	0.66	26.15	2.92
J	24067	47.91	10.75	16.00	2.40	0.64	22.94	2.79
J	24066	45.69	10.23	16.50	2.30	0.59	25.28	2.91
J	24076	46.12	10.30	16.38	2.35	0.61	24.85	2.88
J	24077	47.35	10.31	15.45	2.34	0.62	24.55	2.78
J	24070	45.21	9.39	16.23	2.14	0.55	27.03	2.92
J	24075	46.34	10.00	17.73	2.32	0.59	23.61	2.94
J	34043	44.07	10.96	18.39	2.56	0.66	24.02	3.05
J	34044	44.91	11.07	17.00	2.49	0.66	25.36	2.91
J	24069	43.15	11.79	18.46	2.43	0.67	24.17	3.10
J	34039	44.55	11.01	16.03	2.43	0.64	25.98	2.92
J	14044	47.60	10.43	15.18	2.32	0.56	24.47	2.76
J	14045	46.84	9.91	15.50	2.27	0.57	25.48	2.81

# Analisando as correlações entre variáveis da base de dados
chart.Correlation(pizza[, 2:8], histogram = TRUE, pch = "+")

# Salvando a Matriz de Correlações
rho_pizza <- cor(pizza[,2:8])

# Construindo um mapa de calor a partir das correlações
rho_pizza %>% 
  melt() %>% 
  ggplot() +
  geom_tile(aes(x = Var1, y = Var2, fill = value)) +
  geom_text(aes(x = Var1, y = Var2, label = round(x = value, digits = 3)),
            size = 4) +
  labs(x = NULL,
       y = NULL,
       fill = "Correlações") +
  scale_fill_gradient2(low = "dodgerblue4", 
                       mid = "white", 
                       high = "brown4",
                       midpoint = 0) +
  theme(panel.background = element_rect("white"),
        panel.grid = element_line("grey95"),
        panel.border = element_rect(NA),
        legend.position = "bottom",
        axis.text.x = element_text(angle = 0))

# O teste de efericidade de Bartlett
cortest.bartlett(R = rho_pizza)

## Warning in cortest.bartlett(R = rho_pizza): n not specified, 100 used

## $chisq
## [1] 1608.949
## 
## $p.value
## [1] 0
## 
## $df
## [1] 21

# O algoritmo prcomp(), do pacote psych, EXIGE que a a matriz de dados fornecida
# a ele já esteja padronizada pelo procedimento zscores:
pizza_std <- pizza %>% 
  select(-brand) %>% 
  select(-id) %>% 
  scale() %>% 
  data.frame()

# Rodando a PCA
afpc_pizza <- prcomp(pizza_std)
summary(afpc_pizza)

## Importance of components:
##                          PC1    PC2     PC3    PC4     PC5     PC6      PC7
## Standard deviation     2.042 1.5134 0.64387 0.3085 0.16636 0.01837 0.003085
## Proportion of Variance 0.596 0.3272 0.05922 0.0136 0.00395 0.00005 0.000000
## Cumulative Proportion  0.596 0.9232 0.98240 0.9960 0.99995 1.00000 1.000000

# Sumarizando pontos importantes:
data.frame(eigenvalue = afpc_pizza$sdev ^ 2,
           var_compartilhada = summary(afpc_pizza)$importance[2,],
           var_cumulativa = summary(afpc_pizza)$importance[3,]) -> relatorio

relatorio %>% 
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

	eigenvalue	var_compartilhada	var_cumulativa
PC1	4.1717819	0.59597	0.59597
PC2	2.2904574	0.32721	0.92318
PC3	0.4145623	0.05922	0.98240
PC4	0.0951742	0.01360	0.99600
PC5	0.0276770	0.00395	0.99995
PC6	0.0003376	0.00005	1.00000
PC7	0.0000095	0.00000	1.00000

# Visualizando os pesos que cada variável tem em cada componente principal 
# obtido pela PCA
ggplotly(
  data.frame(afpc_pizza$rotation) %>%
    mutate(var = names(pizza[2:8])) %>%
    melt(id.vars = "var") %>%
    mutate(var = factor(var)) %>%
    ggplot(aes(x = var, y = value, fill = var)) +
    geom_bar(stat = "identity", color = "black") +
    facet_wrap(~variable) +
    labs(x = NULL, y = NULL, fill = "Legenda:") +
    scale_fill_viridis_d() +
    theme_bw() +
    theme(axis.text.x = element_text(angle = 90))
)

# Scree Plot - apenas ignorar os warnings
ggplotly(
  fviz_eig(X = afpc_pizza,
           ggtheme = theme_bw(), 
           barcolor = "black", 
           barfill = "dodgerblue4",
           linecolor = "darkgoldenrod4")
)

## Warning: 'bar' objects don't have these attributes: 'mode'
## Valid attributes include:
## 'type', 'visible', 'showlegend', 'legendgroup', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'selectedpoints', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'xperiod', 'yperiod', 'xperiod0', 'yperiod0', 'xperiodalignment', 'yperiodalignment', 'text', 'texttemplate', 'hovertext', 'hovertemplate', 'textposition', 'insidetextanchor', 'textangle', 'textfont', 'insidetextfont', 'outsidetextfont', 'constraintext', 'cliponaxis', 'orientation', 'base', 'offset', 'width', 'marker', 'offsetgroup', 'alignmentgroup', 'selected', 'unselected', 'r', 't', '_deprecated', 'error_x', 'error_y', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'xsrc', 'ysrc', 'textsrc', 'texttemplatesrc', 'hovertextsrc', 'hovertemplatesrc', 'textpositionsrc', 'basesrc', 'offsetsrc', 'widthsrc', 'rsrc', 'tsrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'

#Extraindo as Cargas Fatoriais
k <- sum((afpc_pizza$sdev ^ 2) > 1) 
cargas_fatoriais <- afpc_pizza$rotation[, 1:k] %*% diag(afpc_pizza$sdev[1:k])

# Visualizando as cargas fatoriais
data.frame(cargas_fatoriais) %>%
  rename(F1 = X1,
         F2 = X2) %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

	F1	F2
mois	0.1321685	-0.9508488
prot	0.7736169	-0.4081810
fat	0.9123125	0.3547153
ash	0.9638315	-0.1679758
sodium	0.8899205	0.3051999
carb	-0.8678837	0.4847685
cal	0.4993639	0.8588049

#Visualizando as Comunalidades
data.frame(rowSums(cargas_fatoriais ^ 2)) %>%
  rename(comunalidades = 1) %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

	comunalidades
mois	0.9215821
prot	0.7650948
fat	0.9581370
ash	0.9571871
sodium	0.8851056
carb	0.9882227
cal	0.9869101

# Relatório das cargas fatoriais e das comunalidades
data.frame(cargas_fatoriais) %>%
  rename(F1 = X1,
         F2 = X2) %>%
  mutate(Comunalidades = rowSums(cargas_fatoriais ^ 2)) %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

	F1	F2	Comunalidades
mois	0.1321685	-0.9508488	0.9215821
prot	0.7736169	-0.4081810	0.7650948
fat	0.9123125	0.3547153	0.9581370
ash	0.9638315	-0.1679758	0.9571871
sodium	0.8899205	0.3051999	0.8851056
carb	-0.8678837	0.4847685	0.9882227
cal	0.4993639	0.8588049	0.9869101

# Plotagem das Cargas Fatoriais
data.frame(cargas_fatoriais) %>%
  ggplot(aes(x = X1, y = X2)) +
  geom_point(color = "orange") +
  geom_hline(yintercept = 0, color = "darkorchid") +
  geom_vline(xintercept = 0, color = "darkorchid") +
  geom_text_repel(label = row.names(cargas_fatoriais)) +
  labs(x = "F1",
       y = "F2") +
  theme_bw()

# Scores Fatoriais
scores_fatoriais <- t(afpc_pizza$rotation)/afpc_pizza$sdev 
colnames(scores_fatoriais) <- colnames(pizza_std)

scores_fatoriais

##              mois         prot          fat          ash     sodium
## PC1    0.03168155   0.18544040    0.2186865   0.23103594  0.2133190
## PC2   -0.41513492  -0.17820937    0.1548666  -0.07333721  0.1332485
## PC3    0.65490257  -1.15867031    0.3095504  -0.08739825  0.7069320
## PC4    0.71545962   0.03433740    1.6435556  -1.79057637 -1.4465875
## PC5    0.03889236   2.33213030   -1.0420975  -4.03263474  3.6222600
## PC6  -24.29771847   0.00933487   28.5946775  -3.20346416 -0.1704016
## PC7 -135.66769453 -89.70568255 -122.4118863 -18.15780333  0.1699452
##              carb         cal
## PC1   -0.20803670   0.1197004
## PC2    0.21164704   0.3749491
## PC3   -0.08112957  -0.1759927
## PC4   -1.08374719   0.9052196
## PC5   -0.04470254  -0.4688702
## PC6    0.02769399 -39.2896481
## PC7 -251.54116862  -3.9088572

scores_fatoriais %>%
  t() %>%
  data.frame() %>%
  rename(PC1 = 1,
         PC2 = 2) %>%
  select(PC1, PC2) %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

	PC1	PC2
mois	0.0316815	-0.4151349
prot	0.1854404	-0.1782094
fat	0.2186865	0.1548666
ash	0.2310359	-0.0733372
sodium	0.2133190	0.1332485
carb	-0.2080367	0.2116470
cal	0.1197004	0.3749491

# Proposta da construção de um ranking ------------------------------------

#Assumindo-se apenas o F1 como indicador, calculam-se os scores fatoriais:
score_D1 <- scores_fatoriais[1,]
score_D1

##        mois        prot         fat         ash      sodium        carb 
##  0.03168155  0.18544040  0.21868652  0.23103594  0.21331905 -0.20803670 
##         cal 
##  0.11970038

#Estabelecendo o ranking dos indicadores assumido
F1 <- t(apply(pizza_std, 1, function(x) x * score_D1))

F1 %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

mois	prot	fat	ash	sodium	carb	cal
-0.0433887	0.2321879	0.6003502	0.4506667	0.6339248	0.2549414	0.3202773
-0.0411667	0.2272885	0.5764731	0.4925170	0.6454444	0.2520567	0.3029024
-0.0416310	0.1906869	0.6225218	0.4452080	0.5532874	0.2545952	0.3241384
-0.0343349	0.1952981	0.5579561	0.3924402	0.5417678	0.2479029	0.2835970
-0.0345339	0.2278649	0.5218968	0.3978990	0.5590472	0.2435182	0.2700832
-0.0323783	0.1976037	0.5379773	0.4160947	0.5648070	0.2476721	0.2700832
-0.0321461	0.2189306	0.5143438	0.3778836	0.5244884	0.2434028	0.2623610
-0.0402713	0.2316115	0.5206786	0.4815995	0.6224051	0.2297874	0.2797359
-0.0420622	0.2048087	0.6059540	0.4342905	0.5993659	0.2502106	0.3202773
-0.0437204	0.2252711	0.6105832	0.4597646	0.5705669	0.2564414	0.3241384
-0.0449474	0.2255593	0.6178925	0.4197339	0.5648070	0.2532106	0.3299301
-0.0461745	0.2255593	0.6042485	0.4579450	0.5763267	0.2449028	0.3279995
-0.0404703	0.1909751	0.6064413	0.4179143	0.5129687	0.2494029	0.3164163
-0.0331410	0.1808880	0.5413883	0.3960794	0.5648070	0.2314028	0.2797359
-0.0331410	0.2131666	0.5311553	0.4124556	0.5417678	0.2477875	0.2700832
-0.0334063	0.1298763	0.5871934	0.4779603	0.6281650	0.2442105	0.2893886
-0.0271052	0.1927043	0.4753608	0.4743212	0.5878463	0.2380951	0.2314723
-0.0209698	0.1197892	0.5028926	0.4397492	0.5417678	0.2410951	0.2295417
-0.0301894	0.2010621	0.4924159	0.5088931	0.5417678	0.2409797	0.2430556
-0.0327762	0.1635959	0.5374900	0.4797799	0.5993659	0.2364797	0.2681526
-0.0460418	0.1782942	0.6571192	0.4215535	0.5648070	0.2491721	0.3492355
-0.0435214	0.1912633	0.6178925	0.4251926	0.5936061	0.2447875	0.3279995
-0.0332405	0.2076908	0.5367591	0.4233730	0.5532874	0.2485952	0.2720137
-0.0288629	0.1693599	0.5650218	0.3615074	0.4784099	0.2579414	0.2758748
-0.0255796	0.1347757	0.5275006	0.4706820	0.5936061	0.2446721	0.2488472
-0.0347329	0.1846346	0.5840260	0.3942598	0.5417678	0.2547106	0.2951803
-0.0397075	0.1906869	0.6083904	0.3906207	0.5475276	0.2511337	0.3164163
-0.0347992	0.1537970	0.5789095	0.4051773	0.5475276	0.2404028	0.2932497
-0.0374192	0.2226773	0.5638036	0.4397492	0.5878463	0.2539029	0.2913192
0.0287430	0.0094079	0.2153927	0.1795498	0.2480175	0.2172103	0.0113902
0.0390571	0.0290056	0.1337719	0.1140450	0.1501007	0.2181334	-0.0426650
0.0252940	-0.0067314	0.2473100	0.1668127	0.1846595	0.2130565	0.0326262
0.0307992	0.0117135	0.1988249	0.1686323	0.1904193	0.2167488	-0.0001931
0.0323911	-0.0047140	0.1810389	0.1831889	0.1904193	0.2082103	-0.0117763
0.0301359	-0.0006792	0.2185600	0.1613540	0.2192184	0.2183642	0.0094597
0.0325569	-0.0127837	0.2351278	0.1759106	0.2076988	0.2307104	0.0094597
0.0328554	-0.0234471	0.2368333	0.0649164	0.0809829	0.2212488	0.0152513
0.0437000	-0.0026966	0.1223207	0.0849318	0.0752231	0.2143257	-0.0561788
0.0364703	0.0258354	0.1142804	0.2214000	0.2249782	0.2054410	-0.0484567
0.0312635	0.0169011	0.2197782	0.1431582	0.1673801	0.2287489	0.0075291
0.0291410	0.0073905	0.2280621	0.1413387	0.1788997	0.2213642	0.0171818
0.0338835	0.0186303	0.1739732	0.1959260	0.2537773	0.2202104	-0.0175680
0.0294063	-0.0038494	0.2114944	0.1740910	0.2249782	0.2120180	0.0075291
0.0466184	0.0255472	0.0672571	0.1013080	0.1328212	0.2107488	-0.0870676
0.0471159	0.0431275	0.0406999	0.1195037	0.1097820	0.2080949	-0.0986508
0.0438327	0.0197831	0.1150113	0.0922101	0.0867427	0.2207873	-0.0600399
0.0279803	0.0120017	0.2275749	0.1613540	0.1616203	0.2202104	0.0171818
0.0323248	-0.0067314	0.2085706	0.1995651	0.2422576	0.2212488	-0.0021236
0.0383274	0.0232416	0.1064838	0.1704519	0.2595371	0.2039410	-0.0542483
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-0.0148345	-0.1355577	-0.1261962	-0.2334941	-0.1666889	-0.1804078	-0.0059847
-0.0167912	-0.1577492	-0.1495860	-0.2516899	-0.1436497	-0.2083311	-0.0098458
-0.0141712	-0.1439155	-0.1861326	-0.2316746	-0.1494095	-0.2097157	-0.0310818
-0.0179187	-0.1516970	-0.1651793	-0.2353137	-0.1436497	-0.2160619	-0.0137069
-0.0133753	-0.1600548	-0.1376475	-0.2389529	-0.1551693	-0.1909079	-0.0137069
-0.0179187	-0.1689891	-0.1120649	-0.2207571	-0.1436497	-0.1970233	0.0055986
-0.0232250	-0.1617840	-0.1069483	-0.2425920	-0.1436497	-0.2115618	0.0210429
-0.0169238	-0.1600548	-0.1498297	-0.2189375	-0.1436497	-0.2077541	-0.0117763
-0.0171228	-0.1589020	-0.1452004	-0.2243963	-0.1321301	-0.2061387	-0.0079152
-0.0171228	-0.1701419	-0.0265458	-0.2353137	-0.1551693	-0.1551384	0.0384178
-0.0162937	-0.1482386	-0.0884314	-0.2243963	-0.1263702	-0.1721000	0.0113902
-0.0179187	-0.1577492	-0.1559208	-0.2225767	-0.1206104	-0.2134080	-0.0098458
-0.0165590	-0.1718711	-0.0930606	-0.1607111	-0.1378899	-0.1806386	0.0075291
-0.0162274	-0.1635133	-0.1127958	-0.2298550	-0.1378899	-0.1898694	0.0017375
-0.0138396	-0.1715829	-0.0504229	-0.2662465	-0.1609291	-0.1575615	0.0229735
-0.0167248	-0.1701419	-0.1342365	-0.1752677	-0.1551693	-0.2009464	-0.0079152
-0.0151993	-0.1531380	-0.1873509	-0.2334941	-0.1378899	-0.2176773	-0.0291512
-0.0208703	-0.1787880	-0.0572450	-0.2444116	-0.1551693	-0.1867540	0.0364873
-0.0140386	-0.1603430	-0.2653169	-0.1807264	-0.1321301	-0.2501006	-0.0658316
-0.0164595	-0.1557318	-0.1639610	-0.2152984	-0.1436497	-0.2108695	-0.0175680
-0.0171228	-0.1589020	-0.1452004	-0.2243963	-0.1321301	-0.2061387	-0.0079152
0.0455572	-0.0868516	-0.1788233	-0.0770106	-0.0802918	0.0342091	-0.1739421
0.0451592	-0.1015499	-0.1627428	-0.1079434	-0.1148506	0.0324783	-0.1642893
0.0429041	-0.0908864	-0.1749250	-0.1024846	-0.1090908	0.0235936	-0.1642893
0.0444960	-0.0782055	-0.1508043	-0.1097629	-0.1206104	0.0451707	-0.1584977
0.0397867	-0.0917510	-0.1432513	-0.1115825	-0.1033310	0.0268244	-0.1449839
0.0467511	-0.0652364	-0.2175627	-0.1061238	-0.1148506	0.0268244	-0.1913170
0.0508634	-0.1243178	-0.2129335	-0.1279587	-0.1090908	0.0182859	-0.1971086
0.0508966	-0.0983796	-0.1707831	-0.1061238	-0.1206104	0.0501323	-0.1816642
0.0448608	-0.1084667	-0.1961220	-0.0861084	-0.0918114	0.0143628	-0.1778032
0.0424066	-0.0684066	-0.1218106	-0.0697322	-0.0687721	0.0580939	-0.1449839
0.0457230	-0.0880044	-0.1573826	-0.0879280	-0.1090908	0.0437861	-0.1662199
0.0406489	-0.0635072	-0.1559208	-0.0824693	-0.1148506	0.0369783	-0.1527061
0.0472486	-0.0707123	-0.1880818	-0.0788301	-0.0918114	0.0420553	-0.1816642
0.0463200	-0.0747471	-0.1603064	-0.1006650	-0.0975712	0.0489784	-0.1681504
0.0481772	-0.0839695	-0.1914928	-0.0842889	-0.0918114	0.0380168	-0.1855253
0.0487409	-0.1061611	-0.1544589	-0.1170412	-0.1090908	0.0465553	-0.1700810
0.0451261	-0.0992442	-0.1844271	-0.1024846	-0.0802918	0.0234782	-0.1739421
0.0458888	-0.0920392	-0.1858890	-0.1043042	-0.1090908	0.0282090	-0.1758726
0.0439985	-0.0779173	-0.1961220	-0.1006650	-0.1033310	0.0226705	-0.1758726
0.0392892	-0.0747471	-0.1766305	-0.0933867	-0.1033310	0.0172474	-0.1584977
0.0446286	-0.0560140	-0.1739504	-0.0715518	-0.1090908	0.0459784	-0.1700810
0.0443633	-0.0756117	-0.1549462	-0.0915672	-0.1206104	0.0449399	-0.1681504
0.0452256	-0.0856987	-0.1707831	-0.0970259	-0.1148506	0.0360552	-0.1681504
0.0436337	-0.0776291	-0.1632301	-0.1079434	-0.1206104	0.0366322	-0.1623588
0.0541135	-0.1070257	-0.2260903	-0.1079434	-0.1148506	0.0315552	-0.2106224
0.0460878	-0.0807993	-0.1659102	-0.1006650	-0.0975712	0.0430938	-0.1681504
0.0439985	-0.0934802	-0.1700521	-0.1024846	-0.1206104	0.0286706	-0.1662199
0.0420086	-0.0761881	-0.1815034	-0.0861084	-0.1090908	0.0242859	-0.1662199
0.0477129	-0.1018381	-0.1783360	-0.1006650	-0.0918114	0.0344399	-0.1778032
0.0174341	-0.0874280	-0.0996390	-0.0297016	0.0003456	-0.0233682	-0.0793454
0.0096074	-0.0692712	-0.0911115	-0.0315211	-0.0111740	-0.0394068	-0.0581094
0.0222097	-0.0848341	-0.1230288	-0.0569952	-0.0630123	-0.0185221	-0.0986508
0.0196893	-0.0998206	-0.1152322	-0.0660931	-0.0572525	-0.0301760	-0.0889981
0.0172351	-0.1009734	-0.1037810	-0.0806497	-0.0802918	-0.0346760	-0.0774148
0.0230057	-0.0926156	-0.1381348	-0.0660931	-0.0745320	-0.0265990	-0.1063730
0.0164392	-0.0828167	-0.0769801	-0.0551756	-0.0342133	-0.0158682	-0.0658316
0.0187275	-0.0756117	-0.0855077	-0.0715518	-0.0342133	-0.0100989	-0.0754843
0.0173346	-0.0767645	-0.0728382	-0.0497169	-0.0342133	-0.0080220	-0.0677621
0.0254598	-0.1041437	-0.1028064	-0.0606344	-0.0399731	-0.0055989	-0.0967203
0.0127911	-0.0133601	-0.1137704	-0.0533561	-0.0342133	-0.0180605	-0.0735537
0.0173346	-0.0730179	-0.1520225	-0.0460777	-0.0169338	-0.0437915	-0.0986508
0.0216459	-0.0842577	-0.0908678	-0.0515365	-0.0342133	-0.0046758	-0.0851370
0.0176331	-0.0609134	-0.1047555	-0.0297016	-0.0226937	-0.0144836	-0.0812759
0.0142504	-0.0779173	-0.0937916	-0.0351603	-0.0399731	-0.0282144	-0.0696927
0.0203857	-0.0839695	-0.1235161	-0.0533561	-0.0169338	-0.0245221	-0.0947897
0.0084467	-0.0738825	-0.0180183	-0.0224233	0.0061054	-0.0100989	-0.0252901
0.0226740	-0.0905982	-0.0954971	-0.0242428	0.0003456	-0.0040989	-0.0889981
0.0141509	-0.0851223	-0.0738128	-0.0533561	-0.0342133	-0.0231375	-0.0600399
0.0128243	-0.0822403	-0.1001263	-0.0351603	-0.0054142	-0.0379068	-0.0677621
0.0232378	-0.0756117	-0.1030500	-0.0424386	-0.0169338	-0.0008681	-0.0928592
0.0158754	-0.0905982	-0.0908678	-0.0606344	-0.0457329	-0.0278683	-0.0696927
0.0173015	-0.0885808	-0.0937916	-0.0515365	-0.0342133	-0.0229067	-0.0754843
0.0213806	-0.0882926	-0.1164505	-0.0533561	-0.0284535	-0.0194451	-0.0947897
0.0142835	-0.1148071	-0.0974462	-0.0897476	-0.0687721	-0.0480607	-0.0677621
0.0180311	-0.0972268	-0.0608996	-0.0569952	-0.0457329	-0.0085989	-0.0639010
0.0105028	-0.0695594	-0.0448191	-0.0133254	-0.0054142	-0.0133297	-0.0426650
0.0132886	-0.0663892	-0.0786856	-0.0260624	-0.0054142	-0.0287914	-0.0696927
0.0074517	-0.0456387	-0.0431136	-0.0369799	0.0003456	-0.0150605	-0.0330123
0.0120947	-0.0681184	-0.1023191	-0.0369799	-0.0169338	-0.0359452	-0.0677621
0.0222097	-0.0848341	-0.1230288	-0.0569952	-0.0630123	-0.0185221	-0.0986508
0.0196893	-0.0998206	-0.1152322	-0.0660931	-0.0572525	-0.0301760	-0.0889981

#Na construção de rankings no R, devemos efetuar a multiplicação por -1, 
#visto que os scores fatoriais das observações mais fortes são, por padrão, 
#apresentados acompanhados do sinal de menos.
F1 <- data.frame(F1) %>%
  mutate(fator1 = rowSums(.) * -1)

F1 %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

mois	prot	fat	ash	sodium	carb	cal	fator1
-0.0433887	0.2321879	0.6003502	0.4506667	0.6339248	0.2549414	0.3202773	-2.4489596
-0.0411667	0.2272885	0.5764731	0.4925170	0.6454444	0.2520567	0.3029024	-2.4555154
-0.0416310	0.1906869	0.6225218	0.4452080	0.5532874	0.2545952	0.3241384	-2.3488066
-0.0343349	0.1952981	0.5579561	0.3924402	0.5417678	0.2479029	0.2835970	-2.1846272
-0.0345339	0.2278649	0.5218968	0.3978990	0.5590472	0.2435182	0.2700832	-2.1857754
-0.0323783	0.1976037	0.5379773	0.4160947	0.5648070	0.2476721	0.2700832	-2.2018598
-0.0321461	0.2189306	0.5143438	0.3778836	0.5244884	0.2434028	0.2623610	-2.1092642
-0.0402713	0.2316115	0.5206786	0.4815995	0.6224051	0.2297874	0.2797359	-2.3255467
-0.0420622	0.2048087	0.6059540	0.4342905	0.5993659	0.2502106	0.3202773	-2.3728449
-0.0437204	0.2252711	0.6105832	0.4597646	0.5705669	0.2564414	0.3241384	-2.4030452
-0.0449474	0.2255593	0.6178925	0.4197339	0.5648070	0.2532106	0.3299301	-2.3661860
-0.0461745	0.2255593	0.6042485	0.4579450	0.5763267	0.2449028	0.3279995	-2.3908073
-0.0404703	0.1909751	0.6064413	0.4179143	0.5129687	0.2494029	0.3164163	-2.2536482
-0.0331410	0.1808880	0.5413883	0.3960794	0.5648070	0.2314028	0.2797359	-2.1611604
-0.0331410	0.2131666	0.5311553	0.4124556	0.5417678	0.2477875	0.2700832	-2.1832749
-0.0334063	0.1298763	0.5871934	0.4779603	0.6281650	0.2442105	0.2893886	-2.3233878
-0.0271052	0.1927043	0.4753608	0.4743212	0.5878463	0.2380951	0.2314723	-2.1726948
-0.0209698	0.1197892	0.5028926	0.4397492	0.5417678	0.2410951	0.2295417	-2.0538658
-0.0301894	0.2010621	0.4924159	0.5088931	0.5417678	0.2409797	0.2430556	-2.1979848
-0.0327762	0.1635959	0.5374900	0.4797799	0.5993659	0.2364797	0.2681526	-2.2520878
-0.0460418	0.1782942	0.6571192	0.4215535	0.5648070	0.2491721	0.3492355	-2.3741397
-0.0435214	0.1912633	0.6178925	0.4251926	0.5936061	0.2447875	0.3279995	-2.3572201
-0.0332405	0.2076908	0.5367591	0.4233730	0.5532874	0.2485952	0.2720137	-2.2084787
-0.0288629	0.1693599	0.5650218	0.3615074	0.4784099	0.2579414	0.2758748	-2.0792524
-0.0255796	0.1347757	0.5275006	0.4706820	0.5936061	0.2446721	0.2488472	-2.1945041
-0.0347329	0.1846346	0.5840260	0.3942598	0.5417678	0.2547106	0.2951803	-2.2198462
-0.0397075	0.1906869	0.6083904	0.3906207	0.5475276	0.2511337	0.3164163	-2.2650679
-0.0347992	0.1537970	0.5789095	0.4051773	0.5475276	0.2404028	0.2932497	-2.1842647
-0.0374192	0.2226773	0.5638036	0.4397492	0.5878463	0.2539029	0.2913192	-2.3218792
0.0287430	0.0094079	0.2153927	0.1795498	0.2480175	0.2172103	0.0113902	-0.9097113
0.0390571	0.0290056	0.1337719	0.1140450	0.1501007	0.2181334	-0.0426650	-0.6414486
0.0252940	-0.0067314	0.2473100	0.1668127	0.1846595	0.2130565	0.0326262	-0.8630275
0.0307992	0.0117135	0.1988249	0.1686323	0.1904193	0.2167488	-0.0001931	-0.8169450
0.0323911	-0.0047140	0.1810389	0.1831889	0.1904193	0.2082103	-0.0117763	-0.7787581
0.0301359	-0.0006792	0.2185600	0.1613540	0.2192184	0.2183642	0.0094597	-0.8564130
0.0325569	-0.0127837	0.2351278	0.1759106	0.2076988	0.2307104	0.0094597	-0.8786805
0.0328554	-0.0234471	0.2368333	0.0649164	0.0809829	0.2212488	0.0152513	-0.6286411
0.0437000	-0.0026966	0.1223207	0.0849318	0.0752231	0.2143257	-0.0561788	-0.4816258
0.0364703	0.0258354	0.1142804	0.2214000	0.2249782	0.2054410	-0.0484567	-0.7799486
0.0312635	0.0169011	0.2197782	0.1431582	0.1673801	0.2287489	0.0075291	-0.8147592
0.0291410	0.0073905	0.2280621	0.1413387	0.1788997	0.2213642	0.0171818	-0.8233781
0.0338835	0.0186303	0.1739732	0.1959260	0.2537773	0.2202104	-0.0175680	-0.8788326
0.0294063	-0.0038494	0.2114944	0.1740910	0.2249782	0.2120180	0.0075291	-0.8556676
0.0466184	0.0255472	0.0672571	0.1013080	0.1328212	0.2107488	-0.0870676	-0.4972331
0.0471159	0.0431275	0.0406999	0.1195037	0.1097820	0.2080949	-0.0986508	-0.4696731
0.0438327	0.0197831	0.1150113	0.0922101	0.0867427	0.2207873	-0.0600399	-0.5183273
0.0279803	0.0120017	0.2275749	0.1613540	0.1616203	0.2202104	0.0171818	-0.8279233
0.0323248	-0.0067314	0.2085706	0.1995651	0.2422576	0.2212488	-0.0021236	-0.8951119
0.0383274	0.0232416	0.1064838	0.1704519	0.2595371	0.2039410	-0.0542483	-0.7477345
0.0300364	0.0007618	0.2097888	0.1540757	0.1788997	0.2139796	0.0055986	-0.7931406
0.0287430	-0.0058668	0.2231893	0.1740910	0.2249782	0.2144411	0.0152513	-0.8748271
0.0279803	-0.0090371	0.2248948	0.1595344	0.2134586	0.2104026	0.0171818	-0.8444155
0.0330544	0.0137309	0.1805516	0.1959260	0.2480175	0.2184796	-0.0137069	-0.8760530
0.0335850	0.0151719	0.1786024	0.1995651	0.2364978	0.2202104	-0.0156374	-0.8679952
0.0433684	0.0194949	0.1096512	0.1249625	0.1443409	0.2185950	-0.0639010	-0.5965117
0.0375647	0.0076787	0.1659329	0.1704519	0.1788997	0.2232104	-0.0291512	-0.7545870
0.0359396	0.0166129	0.1832317	0.1759106	0.2134586	0.2296720	-0.0194985	-0.8353269
0.0352100	0.0099843	0.1961448	0.1795498	0.2192184	0.2308258	-0.0117763	-0.8591567
0.0363376	-0.0070196	0.2093016	0.0558185	0.0752231	0.2263258	-0.0040541	-0.5919328
0.0359728	-0.0055786	0.1985812	0.0740143	0.1097820	0.2217104	-0.0079152	-0.6265668
0.0248628	0.3653372	0.0285177	0.1467974	-0.0975712	0.2556337	-0.0523178	-0.6712599
0.0258246	0.4353702	-0.0696708	0.1631736	-0.1378899	0.2415567	-0.0947897	-0.5635747
0.0264547	0.3417046	0.0160919	0.1067667	-0.1148506	0.2432874	-0.0600399	-0.5594148
0.0267532	0.3532327	-0.0231348	0.1540757	-0.0687721	0.2333643	-0.0774148	-0.5981041
0.0263221	0.3056794	0.0765156	0.0667360	-0.0860516	0.2544798	-0.0349429	-0.6087385
0.0292737	0.3538091	-0.0060797	-0.0224233	-0.0860516	0.2392490	-0.0696927	-0.4380845
0.0307660	0.4301826	-0.1081666	0.1522561	-0.1263702	0.2377489	-0.1218174	-0.4945995
0.0240337	0.4209602	-0.0375098	0.1722715	-0.1090908	0.2442105	-0.0774148	-0.6374604
0.0292405	0.4016506	-0.0813657	0.0812926	-0.2415665	0.2292104	-0.1044425	-0.3140195
0.0354422	0.3708130	-0.0930606	0.1777302	-0.0399731	0.2390182	-0.1276090	-0.5623609
0.0376642	0.3728304	-0.1330182	0.1595344	-0.0802918	0.2274796	-0.1469144	-0.4372842
0.0280134	0.3417046	-0.0048615	0.0703752	-0.1321301	0.2364797	-0.0696927	-0.4698887
0.0232378	0.3647608	0.0319287	0.1959260	-0.0399731	0.2544798	-0.0503872	-0.7799728
0.0229725	0.3587085	0.0136554	0.1267820	-0.0745320	0.2380951	-0.0542483	-0.6314334
0.0232046	0.3509271	0.0212084	0.0740143	-0.1378899	0.2360182	-0.0484567	-0.5190261
0.0271843	0.3215305	0.0207211	0.0376228	-0.1897282	0.2355566	-0.0561788	-0.3967083
0.0303017	0.3100024	-0.0116835	0.1049471	-0.0860516	0.2307104	-0.0793454	-0.4988812
0.0374320	0.3638962	-0.0874568	0.2796265	-0.0342133	0.2522875	-0.1334006	-0.6781715
0.0205847	0.3687956	0.0258376	0.1322408	-0.1090908	0.2399413	-0.0426650	-0.6356441
0.0251282	0.3857995	-0.0058361	0.1831889	-0.1206104	0.2507875	-0.0696927	-0.6487649
0.0375315	0.3711012	-0.0920861	0.2341371	-0.1666889	0.2504413	-0.1334006	-0.5010355
0.0287430	0.3901226	-0.0543212	-0.0770106	-0.1494095	0.2256335	-0.0851370	-0.2786208
0.0358401	0.3344996	-0.0738128	0.0685556	-0.1897282	0.2280566	-0.1160257	-0.2873852
0.0277481	0.4048208	-0.0684526	0.0758339	-0.1954880	0.2310566	-0.0947897	-0.3807291
0.0210490	0.3048148	0.0977126	0.1522561	-0.0572525	0.2512490	-0.0175680	-0.7522611
0.0334192	0.3736950	-0.0915988	0.1031275	-0.1378899	0.2290950	-0.1179563	-0.3918919
0.0287430	0.3483333	0.0136554	0.0740143	-0.1724487	0.2506721	-0.0639010	-0.4790684
0.0190260	0.2307469	0.1152550	0.3578683	0.0579437	0.2359028	-0.0137069	-1.0030358
0.0166713	0.2370874	0.1374266	0.3414921	0.0349045	0.2397105	0.0017375	-1.0090298
0.0222097	0.2506328	0.0219393	0.2614307	0.0291446	0.2046333	-0.0542483	-0.7357423
0.0222429	0.2612963	-0.0150946	0.2596111	-0.0399731	0.1913640	-0.0696927	-0.6097541
0.0199214	0.2425632	0.0229139	0.2596111	0.0521839	0.1937871	-0.0484567	-0.7425240
0.0198219	0.2402576	0.0821194	0.3560487	0.0464241	0.2266720	-0.0291512	-0.9421924
0.0218449	0.2414104	0.0146300	0.2505133	0.0003456	0.1955179	-0.0561788	-0.6680832
0.0236358	0.2474626	0.0158482	0.2523328	0.0176250	0.2048641	-0.0600399	-0.7017287
0.0273833	0.4212484	-0.0667471	0.1195037	-0.1609291	0.2399413	-0.0947897	-0.4856107
0.0207837	0.2569733	0.0260813	0.2632503	0.0406643	0.2042872	-0.0484567	-0.7635833
0.0211816	0.2336289	0.0355834	0.2541524	0.0003456	0.2002487	-0.0465261	-0.6986145
0.0219776	0.2229655	0.0319287	0.2523328	0.0176250	0.1969025	-0.0484567	-0.6952755
0.0230720	0.2558205	-0.0170437	0.2559720	0.0061054	0.1909025	-0.0716232	-0.6432054
0.0238348	0.2673486	0.0331470	0.4706820	0.1501007	0.2355566	-0.0619705	-1.1186991
0.0226409	0.2595671	0.0282741	0.4688625	0.1846595	0.2258643	-0.0619705	-1.1278978
0.0249955	0.2696542	0.0199902	0.4706820	0.1788997	0.2342874	-0.0696927	-1.1288163
0.0216459	0.2523621	0.0190156	0.2650699	0.0291446	0.2022102	-0.0542483	-0.7352000
0.0224750	0.2440042	0.0053715	0.2596111	0.0233848	0.1949410	-0.0619705	-0.6878172
0.0237021	0.2500564	0.0082953	0.2559720	0.0176250	0.2027872	-0.0639010	-0.6945370
0.0235695	0.2287295	0.0199902	0.2505133	0.0349045	0.1989795	-0.0581094	-0.6985769
0.0217123	0.2592789	0.0180410	0.2596111	0.0176250	0.2044026	-0.0542483	-0.7264226
0.0228730	0.2589907	0.0039097	0.2523328	0.0176250	0.2011718	-0.0619705	-0.6949325
0.0245644	0.2627373	-0.0170437	0.2814461	-0.0284535	0.2004795	-0.0754843	-0.6482457
0.0175336	0.2252711	0.1206151	0.3687857	0.0752231	0.2317489	-0.0079152	-1.0312624
0.0262226	0.2610081	-0.0377534	0.2668894	0.0291446	0.1948256	-0.0870676	-0.6532693
0.0264879	0.2759946	0.0414308	0.4779603	0.1040222	0.2526337	-0.0658316	-1.1126980
0.0232378	0.2549559	0.0041533	0.2614307	-0.0630123	0.2015179	-0.0639010	-0.6183823
0.0178321	0.2344935	0.1269499	0.3542291	-0.0399731	0.2385566	-0.0059847	-0.9261035
0.0178652	0.2321879	0.1405940	0.3778836	0.0118652	0.2457105	-0.0021236	-1.0239829
0.0203194	0.2151840	0.1327973	0.3433117	0.0118652	0.2415567	-0.0098458	-0.9551885
0.0195566	0.2111492	0.1186660	0.3487704	0.0176250	0.2309412	-0.0137069	-0.9330015
0.0374320	0.3638962	-0.0874568	0.2796265	-0.0342133	0.2522875	-0.1334006	-0.6781715
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-0.0169238	-0.1600548	-0.1498297	-0.2189375	-0.1436497	-0.2077541	-0.0117763	0.9089260
-0.0171228	-0.1589020	-0.1452004	-0.2243963	-0.1321301	-0.2061387	-0.0079152	0.8918056
-0.0171228	-0.1701419	-0.0265458	-0.2353137	-0.1551693	-0.1551384	0.0384178	0.7210141
-0.0162937	-0.1482386	-0.0884314	-0.2243963	-0.1263702	-0.1721000	0.0113902	0.7644400
-0.0179187	-0.1577492	-0.1559208	-0.2225767	-0.1206104	-0.2134080	-0.0098458	0.8980297
-0.0165590	-0.1718711	-0.0930606	-0.1607111	-0.1378899	-0.1806386	0.0075291	0.7532011
-0.0162274	-0.1635133	-0.1127958	-0.2298550	-0.1378899	-0.1898694	0.0017375	0.8484132
-0.0138396	-0.1715829	-0.0504229	-0.2662465	-0.1609291	-0.1575615	0.0229735	0.7976090
-0.0167248	-0.1701419	-0.1342365	-0.1752677	-0.1551693	-0.2009464	-0.0079152	0.8604018
-0.0151993	-0.1531380	-0.1873509	-0.2334941	-0.1378899	-0.2176773	-0.0291512	0.9739007
-0.0208703	-0.1787880	-0.0572450	-0.2444116	-0.1551693	-0.1867540	0.0364873	0.8067509
-0.0140386	-0.1603430	-0.2653169	-0.1807264	-0.1321301	-0.2501006	-0.0658316	1.0684872
-0.0164595	-0.1557318	-0.1639610	-0.2152984	-0.1436497	-0.2108695	-0.0175680	0.9235379
-0.0171228	-0.1589020	-0.1452004	-0.2243963	-0.1321301	-0.2061387	-0.0079152	0.8918056
0.0455572	-0.0868516	-0.1788233	-0.0770106	-0.0802918	0.0342091	-0.1739421	0.5171530
0.0451592	-0.1015499	-0.1627428	-0.1079434	-0.1148506	0.0324783	-0.1642893	0.5737385
0.0429041	-0.0908864	-0.1749250	-0.1024846	-0.1090908	0.0235936	-0.1642893	0.5751785
0.0444960	-0.0782055	-0.1508043	-0.1097629	-0.1206104	0.0451707	-0.1584977	0.5282142
0.0397867	-0.0917510	-0.1432513	-0.1115825	-0.1033310	0.0268244	-0.1449839	0.5282886
0.0467511	-0.0652364	-0.2175627	-0.1061238	-0.1148506	0.0268244	-0.1913170	0.6215150
0.0508634	-0.1243178	-0.2129335	-0.1279587	-0.1090908	0.0182859	-0.1971086	0.7022601
0.0508966	-0.0983796	-0.1707831	-0.1061238	-0.1206104	0.0501323	-0.1816642	0.5765323
0.0448608	-0.1084667	-0.1961220	-0.0861084	-0.0918114	0.0143628	-0.1778032	0.6010882
0.0424066	-0.0684066	-0.1218106	-0.0697322	-0.0687721	0.0580939	-0.1449839	0.3732051
0.0457230	-0.0880044	-0.1573826	-0.0879280	-0.1090908	0.0437861	-0.1662199	0.5191166
0.0406489	-0.0635072	-0.1559208	-0.0824693	-0.1148506	0.0369783	-0.1527061	0.4918267
0.0472486	-0.0707123	-0.1880818	-0.0788301	-0.0918114	0.0420553	-0.1816642	0.5217959
0.0463200	-0.0747471	-0.1603064	-0.1006650	-0.0975712	0.0489784	-0.1681504	0.5061417
0.0481772	-0.0839695	-0.1914928	-0.0842889	-0.0918114	0.0380168	-0.1855253	0.5508940
0.0487409	-0.1061611	-0.1544589	-0.1170412	-0.1090908	0.0465553	-0.1700810	0.5615368
0.0451261	-0.0992442	-0.1844271	-0.1024846	-0.0802918	0.0234782	-0.1739421	0.5717855
0.0458888	-0.0920392	-0.1858890	-0.1043042	-0.1090908	0.0282090	-0.1758726	0.5930979
0.0439985	-0.0779173	-0.1961220	-0.1006650	-0.1033310	0.0226705	-0.1758726	0.5872390
0.0392892	-0.0747471	-0.1766305	-0.0933867	-0.1033310	0.0172474	-0.1584977	0.5500564
0.0446286	-0.0560140	-0.1739504	-0.0715518	-0.1090908	0.0459784	-0.1700810	0.4900810
0.0443633	-0.0756117	-0.1549462	-0.0915672	-0.1206104	0.0449399	-0.1681504	0.5215827
0.0452256	-0.0856987	-0.1707831	-0.0970259	-0.1148506	0.0360552	-0.1681504	0.5552280
0.0436337	-0.0776291	-0.1632301	-0.1079434	-0.1206104	0.0366322	-0.1623588	0.5515059
0.0541135	-0.1070257	-0.2260903	-0.1079434	-0.1148506	0.0315552	-0.2106224	0.6808636
0.0460878	-0.0807993	-0.1659102	-0.1006650	-0.0975712	0.0430938	-0.1681504	0.5239146
0.0439985	-0.0934802	-0.1700521	-0.1024846	-0.1206104	0.0286706	-0.1662199	0.5801782
0.0420086	-0.0761881	-0.1815034	-0.0861084	-0.1090908	0.0242859	-0.1662199	0.5528160
0.0477129	-0.1018381	-0.1783360	-0.1006650	-0.0918114	0.0344399	-0.1778032	0.5683010
0.0174341	-0.0874280	-0.0996390	-0.0297016	0.0003456	-0.0233682	-0.0793454	0.3017025
0.0096074	-0.0692712	-0.0911115	-0.0315211	-0.0111740	-0.0394068	-0.0581094	0.2909867
0.0222097	-0.0848341	-0.1230288	-0.0569952	-0.0630123	-0.0185221	-0.0986508	0.4228337
0.0196893	-0.0998206	-0.1152322	-0.0660931	-0.0572525	-0.0301760	-0.0889981	0.4378833
0.0172351	-0.1009734	-0.1037810	-0.0806497	-0.0802918	-0.0346760	-0.0774148	0.4605516
0.0230057	-0.0926156	-0.1381348	-0.0660931	-0.0745320	-0.0265990	-0.1063730	0.4813418
0.0164392	-0.0828167	-0.0769801	-0.0551756	-0.0342133	-0.0158682	-0.0658316	0.3144463
0.0187275	-0.0756117	-0.0855077	-0.0715518	-0.0342133	-0.0100989	-0.0754843	0.3337402
0.0173346	-0.0767645	-0.0728382	-0.0497169	-0.0342133	-0.0080220	-0.0677621	0.2919823
0.0254598	-0.1041437	-0.1028064	-0.0606344	-0.0399731	-0.0055989	-0.0967203	0.3844169
0.0127911	-0.0133601	-0.1137704	-0.0533561	-0.0342133	-0.0180605	-0.0735537	0.2935229
0.0173346	-0.0730179	-0.1520225	-0.0460777	-0.0169338	-0.0437915	-0.0986508	0.4131596
0.0216459	-0.0842577	-0.0908678	-0.0515365	-0.0342133	-0.0046758	-0.0851370	0.3290422
0.0176331	-0.0609134	-0.1047555	-0.0297016	-0.0226937	-0.0144836	-0.0812759	0.2961905
0.0142504	-0.0779173	-0.0937916	-0.0351603	-0.0399731	-0.0282144	-0.0696927	0.3304990
0.0203857	-0.0839695	-0.1235161	-0.0533561	-0.0169338	-0.0245221	-0.0947897	0.3767017
0.0084467	-0.0738825	-0.0180183	-0.0224233	0.0061054	-0.0100989	-0.0252901	0.1351610
0.0226740	-0.0905982	-0.0954971	-0.0242428	0.0003456	-0.0040989	-0.0889981	0.2804155
0.0141509	-0.0851223	-0.0738128	-0.0533561	-0.0342133	-0.0231375	-0.0600399	0.3155310
0.0128243	-0.0822403	-0.1001263	-0.0351603	-0.0054142	-0.0379068	-0.0677621	0.3157858
0.0232378	-0.0756117	-0.1030500	-0.0424386	-0.0169338	-0.0008681	-0.0928592	0.3085236
0.0158754	-0.0905982	-0.0908678	-0.0606344	-0.0457329	-0.0278683	-0.0696927	0.3695188
0.0173015	-0.0885808	-0.0937916	-0.0515365	-0.0342133	-0.0229067	-0.0754843	0.3492116
0.0213806	-0.0882926	-0.1164505	-0.0533561	-0.0284535	-0.0194451	-0.0947897	0.3794068
0.0142835	-0.1148071	-0.0974462	-0.0897476	-0.0687721	-0.0480607	-0.0677621	0.4723124
0.0180311	-0.0972268	-0.0608996	-0.0569952	-0.0457329	-0.0085989	-0.0639010	0.3153234
0.0105028	-0.0695594	-0.0448191	-0.0133254	-0.0054142	-0.0133297	-0.0426650	0.1786101
0.0132886	-0.0663892	-0.0786856	-0.0260624	-0.0054142	-0.0287914	-0.0696927	0.2617469
0.0074517	-0.0456387	-0.0431136	-0.0369799	0.0003456	-0.0150605	-0.0330123	0.1660076
0.0120947	-0.0681184	-0.1023191	-0.0369799	-0.0169338	-0.0359452	-0.0677621	0.3159639
0.0222097	-0.0848341	-0.1230288	-0.0569952	-0.0630123	-0.0185221	-0.0986508	0.4228337
0.0196893	-0.0998206	-0.1152322	-0.0660931	-0.0572525	-0.0301760	-0.0889981	0.4378833

#Importando a coluna referente ao fator F1:
pizza["fator1"] <- F1$fator1

#Criando um ranking pela soma ponderada dos fatores por sua variância
#compartilhada
pizza %>%
  mutate(pontuacao = fator1 * 
           relatorio$var_compartilhada[1]) -> pizza

#Visualizando o ranking final
pizza %>%
  arrange(desc(pontuacao)) %>%
  kable() %>%
  kable_styling(bootstrap_options = "striped", 
                full_width = T, 
                font_size = 12)

brand	id	mois	prot	fat	ash	sodium	carb	cal	fator1	pontuacao
H	14032	38.84	8.55	4.38	1.41	0.43	46.82	2.61	1.2965064	0.7726789
H	14028	40.72	8.34	4.96	1.42	0.43	44.56	2.56	1.2639485	0.7532754
E	14029	39.59	8.36	4.39	1.52	0.48	46.14	2.58	1.2483823	0.7439984
E	14033	39.25	8.67	4.44	1.54	0.51	46.10	2.59	1.2160468	0.7247274
H	14123	35.66	9.04	6.24	1.50	0.42	47.56	2.83	1.2030631	0.7169895
E	34033	37.32	7.40	8.18	1.63	0.53	45.47	2.85	1.0825669	0.6451774
H	24132	36.67	7.81	9.34	1.64	0.44	44.54	2.93	1.0684872	0.6367863
G	14077	33.09	7.87	12.07	1.37	0.44	45.60	3.23	1.0155589	0.6052427
H	14127	36.12	8.33	11.90	1.42	0.39	42.23	3.09	1.0042388	0.5984962
F	24103	30.15	8.06	12.23	1.50	0.47	48.06	3.35	0.9802194	0.5841813
G	34013	29.14	8.46	12.25	1.51	0.46	48.64	3.39	0.9744640	0.5807513
H	34029	36.32	8.06	12.54	1.35	0.43	41.73	3.12	0.9739007	0.5804156
H	14076	36.63	8.38	12.59	1.36	0.41	41.04	3.11	0.9661009	0.5757671
E	14039	34.94	7.81	13.67	1.36	0.40	42.22	3.23	0.9580283	0.5709561
G	24004	30.85	8.03	13.67	1.41	0.42	46.04	3.39	0.9578230	0.5708338
E	24053	36.50	7.52	12.46	1.51	0.47	42.01	3.10	0.9457552	0.5636417
H	14159	35.50	8.11	13.45	1.34	0.42	41.59	3.20	0.9435271	0.5623139
H	14064	35.84	7.90	14.09	1.25	0.42	40.92	3.22	0.9376429	0.5588070
F	14084	30.96	8.31	13.42	1.49	0.43	45.82	3.37	0.9364858	0.5581174
G	24121	28.33	8.17	13.64	1.45	0.47	48.41	3.49	0.9348399	0.5571366
F	24097	30.68	8.11	12.92	1.56	0.47	46.73	3.36	0.9320150	0.5554530
E	14109	35.30	7.92	13.85	1.46	0.40	41.47	3.22	0.9243595	0.5508905
H	24112	35.94	7.97	13.50	1.45	0.42	41.14	3.18	0.9235379	0.5504009
E	24104	34.48	7.54	13.93	1.45	0.44	42.60	3.26	0.9201781	0.5483986
G	14119	28.09	8.42	14.06	1.47	0.45	47.96	3.52	0.9150943	0.5453687
G	24022	27.72	8.06	15.34	1.35	0.42	47.53	3.60	0.9142186	0.5448469
F	24046	29.59	8.05	14.07	1.44	0.45	46.22	3.49	0.9117128	0.5433535
H	14156	36.87	7.82	14.58	1.32	0.40	39.41	3.20	0.9098145	0.5422221
H	24024	35.80	7.82	14.08	1.43	0.42	40.87	3.21	0.9089260	0.5416926
H	14057	33.75	8.07	14.93	1.31	0.40	41.94	3.34	0.9084135	0.5413872
G	24015	28.35	8.19	14.90	1.40	0.43	47.16	3.56	0.9076982	0.5409609
H	24034	35.50	7.90	13.83	1.41	0.46	41.36	3.22	0.8980297	0.5351987
G	14095	28.21	8.30	15.00	1.41	0.43	47.08	3.57	0.8978826	0.5351111
G	14166	27.56	8.25	14.65	1.45	0.46	48.09	3.57	0.8971030	0.5346465
E	24088	37.59	7.93	13.58	1.43	0.45	39.47	3.12	0.8959431	0.5339552
F	14143	29.54	7.79	15.08	1.41	0.45	46.18	3.52	0.8939694	0.5327789
G	24047	29.06	8.46	14.12	1.47	0.47	46.89	3.48	0.8931190	0.5322721
F	24086	30.53	8.02	14.17	1.49	0.47	45.79	3.43	0.8930277	0.5322177
H	24089	35.74	7.86	14.27	1.40	0.44	40.73	3.23	0.8918056	0.5314894
H	24089	35.74	7.86	14.27	1.40	0.44	40.73	3.23	0.8918056	0.5314894
F	14118	29.79	8.17	14.35	1.49	0.46	46.20	3.46	0.8914722	0.5312907
H	14007	33.05	7.34	15.78	1.34	0.42	42.49	3.41	0.8869181	0.5285766
E	14063	34.51	7.75	14.87	1.42	0.42	41.45	3.31	0.8851802	0.5275408
G	34018	27.72	8.24	15.16	1.46	0.45	47.42	3.59	0.8767831	0.5225364
G	14112	28.63	8.42	15.24	1.43	0.43	46.28	3.56	0.8762444	0.5222154
E	14089	34.58	7.44	16.24	1.31	0.39	40.43	3.38	0.8725147	0.5199926
F	14065	28.66	7.67	16.12	1.41	0.43	46.14	3.60	0.8706210	0.5188640
G	14145	28.15	8.23	15.45	1.41	0.45	46.76	3.59	0.8700620	0.5185309
H	24016	33.90	7.76	15.84	1.30	0.42	41.20	3.38	0.8687180	0.5177299
G	14131	28.19	8.57	14.16	1.76	0.42	47.32	3.51	0.8670608	0.5167422
F	14038	30.28	7.76	16.04	1.40	0.42	44.52	3.53	0.8670045	0.5167087
F	14165	29.89	7.95	15.08	1.45	0.47	45.63	3.50	0.8669144	0.5166550
H	14041	36.43	8.67	15.05	1.35	0.38	38.50	3.24	0.8631639	0.5144198
F	24137	30.97	7.60	14.22	1.78	0.45	45.43	3.40	0.8628444	0.5142294
H	24139	35.86	7.47	14.72	1.67	0.40	40.28	3.23	0.8604018	0.5127737
F	24035	27.65	7.78	17.30	1.29	0.40	46.25	3.72	0.8592674	0.5120976
F	14018	29.78	8.20	14.51	1.50	0.50	46.01	3.47	0.8577608	0.5111997
G	14040	28.03	8.27	16.40	1.37	0.41	45.93	3.64	0.8572488	0.5108946
H	24009	35.50	7.51	15.63	1.42	0.42	39.94	3.30	0.8548042	0.5094377
F	14054	30.09	7.99	15.16	1.46	0.48	45.30	3.50	0.8517620	0.5076246
G	14085	27.28	8.55	15.18	1.51	0.46	47.48	3.61	0.8507943	0.5070479
G	14017	28.29	8.05	16.72	1.31	0.43	45.63	3.65	0.8489361	0.5059405
H	34028	36.01	7.70	15.60	1.37	0.43	39.32	3.28	0.8484132	0.5056288
G	24149	28.64	8.01	16.02	1.43	0.45	45.90	3.60	0.8453969	0.5038312
E	24035	34.31	7.98	14.54	1.46	0.49	41.71	3.30	0.8445887	0.5033495
H	14144	35.48	7.66	15.39	1.37	0.46	40.10	3.30	0.8442998	0.5031773
E	24099	36.69	7.80	14.77	1.46	0.46	39.28	3.21	0.8428951	0.5023402
E	14126	37.78	8.30	13.05	1.64	0.49	39.23	3.08	0.8412653	0.5013689
E	14126	37.78	8.30	13.05	1.64	0.49	39.23	3.08	0.8412653	0.5013689
E	14099	35.14	8.05	15.77	1.38	0.41	39.66	3.33	0.8410399	0.5012345
H	14088	35.68	8.01	16.36	1.30	0.39	38.65	3.34	0.8385186	0.4997319
G	34008	26.45	7.89	17.97	1.30	0.39	46.39	3.79	0.8357945	0.4981085
G	14010	28.68	8.30	16.07	1.41	0.45	45.54	3.60	0.8351734	0.4977383
F	14079	30.29	8.09	14.82	1.52	0.51	45.28	3.47	0.8338646	0.4969583
G	24119	27.16	8.27	14.68	1.79	0.46	48.10	3.58	0.8334415	0.4967061
G	14026	28.13	8.34	16.19	1.42	0.45	45.92	3.63	0.8296943	0.4944729
F	24109	29.30	8.02	16.34	1.43	0.45	44.91	3.59	0.8256306	0.4920511
F	24150	29.69	7.63	15.71	1.63	0.46	45.34	3.53	0.8253202	0.4918661
E	14122	36.04	7.74	15.49	1.45	0.45	39.28	3.27	0.8252337	0.4918146
E	14078	36.54	7.75	15.67	1.43	0.44	38.61	3.26	0.8225004	0.4901856
H	14111	35.61	8.07	16.15	1.41	0.40	38.81	3.33	0.8201396	0.4887786
G	14055	27.71	8.28	15.62	1.53	0.50	46.86	3.61	0.8125971	0.4842835
H	24100	34.61	7.17	17.88	1.29	0.40	39.05	3.46	0.8067509	0.4807993
F	34035	28.98	7.70	16.67	1.48	0.47	45.17	3.62	0.8044650	0.4794370
G	24156	26.19	7.99	17.53	1.42	0.44	46.87	3.77	0.8032607	0.4787193
H	34007	36.73	7.42	18.16	1.17	0.39	36.52	3.39	0.7976090	0.4753511
G	24059	25.00	8.49	16.87	1.45	0.47	48.19	3.79	0.7975093	0.4752916
H	14009	35.55	7.32	16.40	1.76	0.36	38.97	3.33	0.7970629	0.4750256
F	24106	28.84	7.88	17.21	1.42	0.46	44.65	3.65	0.7914704	0.4716926
E	14056	36.84	7.77	17.07	1.37	0.40	36.95	3.33	0.7881079	0.4696886
G	24041	30.63	8.21	17.33	1.39	0.42	42.44	3.59	0.7876808	0.4694341
F	24049	28.33	7.82	17.96	1.41	0.45	44.48	3.71	0.7706523	0.4592856
F	24157	29.00	7.51	17.78	1.58	0.43	44.13	3.67	0.7660207	0.4565253
H	24037	35.99	8.23	16.60	1.40	0.45	37.78	3.33	0.7644400	0.4555833
G	24033	28.55	8.25	17.30	1.48	0.47	44.42	3.66	0.7583143	0.4519325
H	14100	33.44	7.45	18.49	1.39	0.40	39.23	3.53	0.7580665	0.4517849
H	24120	35.91	7.41	16.41	1.75	0.43	38.52	3.31	0.7532011	0.4488853
E	14142	39.36	8.10	16.44	1.45	0.44	34.65	3.19	0.7484826	0.4460732
F	14096	28.46	7.70	18.88	1.40	0.43	43.56	3.75	0.7462659	0.4447521
F	34036	28.34	7.60	18.51	1.45	0.46	44.10	3.73	0.7422753	0.4423738
E	34031	35.54	7.47	17.67	1.44	0.47	37.88	3.40	0.7306079	0.4354204
F	24055	27.93	7.88	17.49	1.44	0.47	45.26	3.96	0.7254590	0.4323518
H	24054	35.74	7.47	19.14	1.34	0.40	36.31	3.47	0.7210141	0.4297028
F	34037	28.03	7.65	18.39	1.53	0.49	44.40	3.74	0.7144811	0.4258093
I	24052	56.24	9.06	11.49	1.93	0.48	21.28	2.25	0.7022601	0.4185259
E	24140	34.23	7.75	17.94	1.61	0.44	38.47	3.46	0.7018755	0.4182967
E	14160	33.24	7.54	19.56	1.32	0.43	38.34	3.60	0.7017405	0.4182163
F	34034	28.36	7.62	19.29	1.45	0.47	43.28	3.77	0.6996847	0.4169911
H	24001	35.10	8.04	19.07	1.36	0.41	36.43	3.50	0.6946086	0.4139659
E	24142	34.77	7.26	18.80	1.58	0.43	37.59	3.49	0.6885261	0.4103409
E	14155	34.47	7.62	19.07	1.44	0.44	37.40	3.52	0.6842977	0.4078209
I	34019	57.22	9.66	10.95	2.04	0.47	20.13	2.18	0.6808636	0.4057743
G	14066	26.33	8.03	19.98	1.43	0.45	44.23	3.89	0.6807432	0.4057025
E	34032	33.65	7.11	19.50	1.48	0.45	38.26	3.57	0.6784710	0.4043484
G	14153	28.83	8.26	20.10	1.37	0.42	41.44	3.80	0.6762791	0.4030420
E	34030	35.21	6.98	20.02	1.35	0.46	36.44	3.54	0.6670608	0.3975482
F	14152	29.92	8.11	19.23	1.51	0.48	41.23	3.70	0.6550337	0.3903804
F	24042	29.10	8.07	20.05	1.45	0.45	41.33	3.78	0.6528335	0.3890692
F	14110	30.07	8.02	20.39	1.45	0.45	40.07	3.76	0.6320962	0.3767104
I	24128	55.00	11.11	11.30	2.05	0.47	20.54	2.28	0.6215150	0.3704043
F	14130	28.93	8.18	19.35	1.39	0.58	42.15	3.75	0.6185753	0.3686523
E	24110	37.34	7.33	19.61	1.60	0.45	34.12	3.42	0.6165667	0.3674552
E	24110	37.34	7.33	19.61	1.60	0.45	34.12	3.42	0.6165667	0.3674552
I	14157	54.43	9.61	12.18	2.16	0.51	21.62	2.35	0.6010882	0.3582305
I	14098	54.74	10.18	12.60	2.06	0.48	20.42	2.36	0.5930979	0.3534686
I	14125	54.17	10.67	12.18	2.08	0.49	20.90	2.36	0.5872390	0.3499768
I	34026	54.17	10.13	13.25	2.07	0.46	20.38	2.41	0.5801782	0.3457688
I	14068	56.25	9.96	13.22	2.05	0.46	18.52	2.33	0.5765323	0.3435959
I	14019	53.84	10.22	13.05	2.07	0.48	20.82	2.42	0.5751785	0.3427891
I	14046	54.52	9.85	13.55	2.04	0.47	20.05	2.42	0.5737385	0.3419309
I	14114	54.51	9.93	12.66	2.07	0.53	20.83	2.37	0.5717855	0.3407670
I	34024	55.29	9.84	12.91	2.08	0.51	19.88	2.35	0.5683010	0.3386903
I	24023	55.60	9.69	13.89	1.99	0.48	18.83	2.39	0.5615368	0.3346591
I	34021	54.54	10.40	13.22	2.10	0.47	19.74	2.40	0.5552280	0.3308992
I	34025	53.57	10.73	12.78	2.16	0.48	20.76	2.41	0.5528160	0.3294618
I	24141	54.06	10.68	13.53	2.04	0.46	19.69	2.43	0.5515059	0.3286810
I	14030	55.43	10.46	12.37	2.17	0.51	19.57	2.31	0.5508940	0.3283163
I	24048	52.75	10.78	12.98	2.12	0.49	21.37	2.45	0.5500564	0.3278171
I	24111	52.90	10.19	14.35	2.02	0.49	20.54	2.52	0.5282886	0.3148442
I	24107	54.32	10.66	14.04	2.03	0.46	18.95	2.45	0.5282142	0.3147998
I	34027	54.80	10.57	13.42	2.08	0.50	19.13	2.40	0.5239146	0.3122374
I	14031	55.15	10.92	12.51	2.20	0.51	19.22	2.33	0.5217959	0.3109747
I	34022	54.28	10.75	13.87	2.13	0.46	18.97	2.40	0.5215827	0.3108476
I	14102	54.69	10.32	13.77	2.15	0.48	19.07	2.41	0.5191166	0.3093779
I	14134	54.64	10.36	12.89	2.21	0.53	19.90	2.37	0.5171530	0.3082077
I	14067	54.87	10.78	13.65	2.08	0.50	18.62	2.40	0.5061417	0.3016453
I	14103	53.16	11.17	13.83	2.18	0.47	19.66	2.48	0.4918267	0.2931140
I	34023	54.36	11.43	13.09	2.24	0.48	18.88	2.39	0.4900810	0.2920736
J	14043	47.84	10.16	14.56	2.27	0.54	25.17	2.72	0.4813418	0.2868653
J	24070	45.21	9.39	16.23	2.14	0.55	27.03	2.92	0.4723124	0.2814840
J	14042	46.10	9.87	15.97	2.19	0.53	25.87	2.87	0.4605516	0.2744749
J	14045	46.84	9.91	15.50	2.27	0.57	25.48	2.81	0.4378833	0.2609653
J	14045	46.84	9.91	15.50	2.27	0.57	25.48	2.81	0.4378833	0.2609653
J	14044	47.60	10.43	15.18	2.32	0.56	24.47	2.76	0.4228337	0.2519962
J	14044	47.60	10.43	15.18	2.32	0.56	24.47	2.76	0.4228337	0.2519962
J	24073	46.13	10.84	13.99	2.38	0.64	26.66	2.76	0.4131596	0.2462307
J	24062	48.58	9.76	16.01	2.30	0.60	23.35	2.77	0.3844169	0.2291009
J	24077	47.35	10.31	15.45	2.34	0.62	24.55	2.78	0.3794068	0.2261151
J	24078	47.05	10.46	15.16	2.34	0.64	24.99	2.78	0.3767017	0.2245029
I	14158	53.69	11.00	15.23	2.25	0.55	17.83	2.52	0.3732051	0.2224190
J	24066	45.69	10.23	16.50	2.30	0.59	25.28	2.91	0.3695188	0.2202221
J	24076	46.12	10.30	16.38	2.35	0.61	24.85	2.88	0.3492116	0.2081197
J	24064	46.55	10.75	16.72	2.24	0.61	23.74	2.88	0.3337402	0.1988991
J	24068	45.20	10.67	16.38	2.44	0.60	25.31	2.91	0.3304990	0.1969675
J	24072	47.43	10.45	16.50	2.35	0.61	23.27	2.83	0.3290422	0.1960993
J	34039	44.55	11.01	16.03	2.43	0.64	25.98	2.92	0.3159639	0.1883050
J	34040	44.77	10.52	16.12	2.44	0.66	26.15	2.92	0.3157858	0.1881988
J	34041	45.17	10.42	17.20	2.34	0.61	24.87	2.96	0.3155310	0.1880470
J	24075	46.34	10.00	17.73	2.32	0.59	23.61	2.94	0.3153234	0.1879233
J	24065	45.86	10.50	17.07	2.33	0.61	24.24	2.93	0.3144463	0.1874006
J	24067	47.91	10.75	16.00	2.40	0.64	22.94	2.79	0.3085236	0.1838708
J	34042	46.16	10.34	16.14	2.47	0.67	24.89	2.86	0.3017025	0.1798056
J	24071	46.22	11.26	15.93	2.47	0.63	24.12	2.85	0.2961905	0.1765207
J	24074	44.76	12.91	15.56	2.34	0.61	24.43	2.89	0.2935229	0.1749308
J	24063	46.13	10.71	17.24	2.36	0.61	23.56	2.92	0.2919823	0.1740127
J	34045	43.80	10.97	16.49	2.46	0.65	26.28	2.97	0.2909867	0.1734193
J	34038	47.74	10.23	16.31	2.50	0.67	23.22	2.81	0.2804155	0.1671192
J	34044	44.91	11.07	17.00	2.49	0.66	25.36	2.91	0.2617469	0.1559933
J	34043	44.07	10.96	18.39	2.56	0.66	24.02	3.05	0.1786101	0.1064462
J	24069	43.15	11.79	18.46	2.43	0.67	24.17	3.10	0.1660076	0.0989356
J	24056	43.45	10.81	19.49	2.51	0.68	23.74	3.14	0.1351610	0.0805519
C	24124	49.57	26.91	18.00	2.21	0.41	3.31	2.83	-0.2786208	-0.1660496
C	24113	51.71	24.98	17.20	3.01	0.34	3.10	2.67	-0.2873852	-0.1712730
C	14073	49.72	27.31	16.89	3.08	0.25	3.00	2.73	-0.3140195	-0.1871462
C	24058	49.27	27.42	17.42	3.05	0.33	2.84	2.78	-0.3807291	-0.2269031
C	34010	50.98	26.34	16.47	3.20	0.43	3.01	2.66	-0.3918919	-0.2335558
C	24031	49.10	24.53	21.08	2.84	0.34	2.45	2.98	-0.3967083	-0.2364263
C	14162	52.26	26.31	14.77	3.51	0.53	3.15	2.51	-0.4372842	-0.2606083
C	14029	49.73	25.65	19.98	2.51	0.52	2.13	2.91	-0.4380845	-0.2610852
B	14161	55.11	14.87	21.90	3.29	0.86	4.83	2.76	-0.4696731	-0.2799111
C	14139	49.35	25.23	20.03	3.02	0.44	2.37	2.91	-0.4698887	-0.2800396
C	34003	49.57	25.46	20.79	3.04	0.37	1.14	2.94	-0.4790684	-0.2855104
B	14094	54.08	13.28	25.25	3.10	0.80	4.29	2.98	-0.4816258	-0.2870345
D	14004	49.16	27.99	17.49	3.29	0.39	2.07	2.78	-0.4856107	-0.2894094
C	14106	50.18	28.30	15.79	3.47	0.45	2.26	2.64	-0.4945995	-0.2947665
B	14149	54.96	14.26	22.99	3.19	0.90	4.60	2.82	-0.4972331	-0.2963360
C	24038	50.04	24.13	19.75	3.21	0.52	2.87	2.86	-0.4988812	-0.2973183
C	24135	52.22	26.25	16.45	3.92	0.38	1.16	2.58	-0.5010355	-0.2986021
B	14113	54.12	14.06	24.95	3.14	0.82	3.73	2.96	-0.5183273	-0.3089075
C	24020	47.90	25.55	21.10	3.04	0.43	2.41	3.02	-0.5190261	-0.3093240
C	14036	48.88	25.23	20.89	3.22	0.47	1.78	2.96	-0.5594148	-0.3333944
C	14151	51.59	26.24	16.41	3.61	0.60	2.15	2.61	-0.5623609	-0.3351502
C	14022	48.69	28.48	17.37	3.53	0.43	1.93	2.78	-0.5635747	-0.3358736
B	34005	51.86	13.13	28.82	2.94	0.80	3.25	3.25	-0.5919328	-0.3527742
B	34011	53.98	14.05	24.73	3.32	0.92	3.92	2.94	-0.5965117	-0.3555031
C	14093	48.97	25.63	19.28	3.48	0.55	2.64	2.87	-0.5981041	-0.3564521
C	14080	48.84	23.98	23.37	3.00	0.52	0.81	3.09	-0.6087385	-0.3627899
D	14116	47.61	22.44	19.61	4.06	0.60	6.28	2.91	-0.6097541	-0.3633951
D	24134	47.91	22.22	20.40	4.07	0.56	5.40	2.94	-0.6183823	-0.3685373
B	24118	51.75	13.18	28.38	3.04	0.86	3.65	3.23	-0.6265668	-0.3734150
B	14083	50.81	12.56	29.95	2.99	0.81	3.69	3.35	-0.6286411	-0.3746512
C	24006	47.83	25.82	20.79	3.33	0.54	2.23	2.99	-0.6314334	-0.3763153
C	24152	47.11	26.17	21.29	3.36	0.48	2.07	3.05	-0.6356441	-0.3788248
C	14014	48.15	27.98	18.69	3.58	0.48	1.70	2.87	-0.6374604	-0.3799073
B	14006	52.68	14.38	25.72	3.26	0.93	3.96	3.05	-0.6414486	-0.3822841
D	14059	47.86	22.25	19.53	4.04	0.68	6.32	2.90	-0.6432054	-0.3833311
D	24044	48.31	22.49	19.53	4.18	0.62	5.49	2.88	-0.6482457	-0.3863350
C	24144	48.48	26.76	19.99	3.64	0.46	1.13	2.91	-0.6487649	-0.3866444
D	24153	48.81	22.43	18.68	4.10	0.72	5.98	2.82	-0.6532693	-0.3893289
D	14050	47.49	21.75	20.83	4.01	0.67	5.92	2.98	-0.6680832	-0.3981575
C	14058	48.40	26.05	21.40	3.44	0.50	0.71	3.00	-0.6712599	-0.4000507
C	24043	52.19	26.00	16.64	4.17	0.61	1.00	2.58	-0.6781715	-0.4041698
D	24043	52.19	26.00	16.64	4.17	0.61	1.00	2.58	-0.6781715	-0.4041698
D	24021	47.68	21.84	20.45	4.06	0.71	5.97	2.95	-0.6878172	-0.4099184
D	24011	48.05	22.05	20.57	4.04	0.70	5.29	2.94	-0.6945370	-0.4139232
D	24039	47.80	22.36	20.39	4.02	0.70	5.43	2.95	-0.6949325	-0.4141589
D	14023	47.53	21.11	21.54	4.02	0.70	5.80	3.02	-0.6952755	-0.4143633
D	24030	48.01	21.31	21.05	4.01	0.73	5.62	2.97	-0.6985769	-0.4163309
D	14037	47.29	21.48	21.69	4.03	0.67	5.51	3.03	-0.6986145	-0.4163533
D	14013	48.03	21.96	20.88	4.02	0.70	5.11	2.96	-0.7017287	-0.4182092
D	34009	47.45	22.37	20.97	4.06	0.70	5.15	2.99	-0.7264226	-0.4329261
D	24007	47.43	22.13	21.01	4.09	0.72	5.34	2.99	-0.7352000	-0.4381572
D	14072	47.60	22.07	21.13	4.07	0.72	5.13	2.99	-0.7357423	-0.4384803
D	14128	46.91	21.79	21.17	4.06	0.76	6.07	3.02	-0.7425240	-0.4425220
B	24045	52.46	14.18	24.60	3.57	1.12	5.19	2.99	-0.7477345	-0.4456273
C	24091	47.25	23.95	24.24	3.47	0.57	1.09	3.18	-0.7522611	-0.4483250
B	24125	52.23	13.64	27.04	3.57	0.98	3.52	3.12	-0.7545870	-0.4497112
D	14003	47.17	22.29	21.30	4.08	0.74	5.16	3.02	-0.7635833	-0.4550727
B	14062	50.67	13.21	27.66	3.64	1.00	4.82	3.21	-0.7787581	-0.4641165
B	14124	51.90	14.27	24.92	3.85	1.06	5.06	3.02	-0.7799486	-0.4648260
C	14115	47.91	26.03	21.54	3.71	0.60	0.81	3.01	-0.7799728	-0.4648404
B	24040	49.96	13.40	28.84	3.48	0.98	4.32	3.30	-0.7931406	-0.4726880
B	24019	50.33	13.96	29.25	3.42	0.96	3.04	3.31	-0.8147592	-0.4855720
B	14052	50.19	13.78	28.39	3.56	1.00	4.08	3.27	-0.8169450	-0.4868747
B	24012	49.69	13.63	29.59	3.41	0.98	3.68	3.36	-0.8233781	-0.4907086
B	24008	49.34	13.79	29.57	3.52	0.95	3.78	3.36	-0.8279233	-0.4934175
B	24145	51.74	13.95	27.75	3.60	1.04	2.96	3.17	-0.8353269	-0.4978298
B	24083	49.34	13.06	29.46	3.51	1.04	4.63	3.36	-0.8444155	-0.5032463
B	14146	49.77	13.24	28.91	3.59	1.06	4.49	3.31	-0.8556676	-0.5099522
B	14047	49.99	13.35	29.20	3.52	1.05	3.94	3.32	-0.8564130	-0.5103965
B	24151	51.52	13.72	28.28	3.62	1.05	2.86	3.21	-0.8591567	-0.5120316
B	14024	48.53	13.14	30.38	3.55	0.99	4.40	3.44	-0.8630275	-0.5143385
B	24101	51.03	13.90	27.56	3.73	1.08	3.78	3.19	-0.8679952	-0.5172991
B	24093	49.57	13.17	29.39	3.59	1.06	4.28	3.35	-0.8748271	-0.5213707
B	24049	50.87	13.85	27.64	3.71	1.10	3.93	3.20	-0.8760530	-0.5221013
B	14074	50.72	12.93	29.88	3.60	1.03	2.87	3.32	-0.8786805	-0.5236672
B	14132	51.12	14.02	27.37	3.71	1.11	3.78	3.18	-0.8788326	-0.5237579
B	24029	50.65	13.14	28.79	3.73	1.09	3.69	3.26	-0.8951119	-0.5334599
B	14015	49.57	13.70	29.07	3.62	1.10	4.04	3.33	-0.9097113	-0.5421607
D	24123	46.28	21.51	25.44	4.58	0.60	2.19	3.24	-0.9261035	-0.5519299
D	24092	46.80	20.70	25.10	4.55	0.70	2.85	3.20	-0.9330015	-0.5560409
D	14107	46.88	21.71	23.60	4.59	0.75	3.22	3.12	-0.9421924	-0.5615184
D	24084	47.03	20.84	25.68	4.52	0.69	1.93	3.22	-0.9551885	-0.5692637
D	14092	46.64	21.38	24.96	4.60	0.77	2.42	3.20	-1.0030358	-0.5977792
D	14081	45.93	21.60	25.87	4.51	0.73	2.09	3.28	-1.0090298	-0.6013515
D	24114	46.29	21.43	26.00	4.71	0.69	1.57	3.26	-1.0239829	-0.6102631
D	34004	46.19	21.19	25.18	4.66	0.80	2.78	3.23	-1.0312624	-0.6146014
D	24143	48.89	22.95	21.93	5.26	0.85	0.97	2.93	-1.1126980	-0.6631346
D	14163	48.09	22.65	21.59	5.22	0.93	2.45	2.95	-1.1186991	-0.6667111
D	14150	47.73	22.38	21.39	5.21	0.99	3.29	2.95	-1.1278978	-0.6721933
D	14140	48.44	22.73	21.05	5.22	0.98	2.56	2.91	-1.1288163	-0.6727407
A	24108	34.58	17.53	40.87	5.05	1.61	1.97	4.46	-2.0538658	-1.2240424
A	24122	32.20	19.25	43.42	4.62	1.50	0.51	4.70	-2.0792524	-1.2391720
A	14082	31.21	20.97	41.34	4.71	1.58	1.77	4.63	-2.1092642	-1.2570582
A	14154	30.91	19.65	42.45	4.81	1.65	2.81	4.72	-2.1611604	-1.2879867
A	24094	32.73	20.06	39.74	5.24	1.69	2.23	4.47	-2.1726948	-1.2948609
A	24005	30.91	20.77	42.03	4.90	1.61	1.39	4.67	-2.1832749	-1.3011663
A	24146	30.41	18.71	43.99	4.86	1.62	2.03	4.79	-2.1842647	-1.3017562
A	14016	30.55	20.15	43.13	4.79	1.61	1.38	4.74	-2.1846272	-1.3019722
A	14005	30.49	21.28	41.65	4.82	1.64	1.76	4.67	-2.1857754	-1.3026566
A	24115	33.19	18.05	41.88	5.22	1.70	1.66	4.56	-2.1945041	-1.3078586
A	24102	31.80	20.35	40.44	5.43	1.61	1.98	4.53	-2.1979848	-1.3099330
A	14075	31.14	20.23	42.31	4.92	1.65	1.40	4.67	-2.2018598	-1.3122424
A	24136	30.88	20.58	42.26	4.96	1.63	1.32	4.68	-2.2084787	-1.3161870
A	34012	30.43	19.78	44.20	4.80	1.61	0.79	4.80	-2.2198462	-1.3229617
A	24082	31.02	19.05	42.29	5.27	1.71	2.37	4.66	-2.2520878	-1.3421768
A	14164	28.70	20.00	45.12	4.93	1.56	1.25	4.91	-2.2536482	-1.3431067
A	34006	28.93	19.99	45.20	4.78	1.62	1.10	4.91	-2.2650679	-1.3499125
A	24138	29.62	21.10	43.37	5.05	1.69	0.86	4.78	-2.3218792	-1.3837704
A	24026	30.83	17.88	44.33	5.26	1.76	1.70	4.77	-2.3233878	-1.3846694
A	14097	28.76	21.41	41.60	5.28	1.75	2.95	4.72	-2.3255467	-1.3859561
A	14025	28.35	19.99	45.78	5.08	1.63	0.80	4.95	-2.3488066	-1.3998183
A	34020	27.78	20.01	45.59	4.97	1.70	1.65	4.97	-2.3572201	-1.4048325
A	14101	27.35	21.20	45.59	4.94	1.65	0.92	4.98	-2.3661860	-1.4101759
A	14117	28.22	20.48	45.10	5.02	1.71	1.18	4.93	-2.3728449	-1.4141444
A	34017	27.02	19.56	47.20	4.95	1.65	1.27	5.08	-2.3741397	-1.4149160
A	14108	26.98	21.20	45.03	5.15	1.67	1.64	4.97	-2.3908073	-1.4248494
A	14133	27.72	21.19	45.29	5.16	1.66	0.64	4.95	-2.4030452	-1.4321428
A	14069	27.82	21.43	44.87	5.11	1.77	0.77	4.93	-2.4489596	-1.4595064
A	14053	28.49	21.26	43.89	5.34	1.79	1.02	4.84	-2.4555154	-1.4634135